CHOP Researchers to Study Racial Disparities in Cystic Fibrosis Diagnosis, Treatment

To screen newborns for cystic fibrosis, a small sample of blood from a baby's heel is taken and sent to a state lab. Newborn screening is performed using an initial biomarker test, and when elevated, a DNA-based test is used to detect common variants that cause the disease.

By ingenol [at] chop.edu (Lauren Ingeno)

For children with cystic fibrosis (CF), an early diagnosis can mean delaying or preventing serious, lifelong health issues.

CF is a genetic disorder that affects nearly 40,000 people in the United States. Patients have a dysfunctional protein that causes a build-up of mucus in different organs of the body, leading to repeated infections, malnutrition, and other complications. Early treatment includes physical therapy and nutritional interventions.

"Left untreated for even a few months, kids with CF can become severely malnourished," said Clement Ren, MD, director of the Cystic Fibrosis Center at Children's Hospital of Philadelphia. "And we know that nutrition in the first three years is critically important to a child's lung function later in life."

Recognizing the crucial benefits of early diagnosis, every U.S. state has offered newborn screenings for CF since 2010. However, this testing is conducted at the state level, and there is significant variation in the algorithms that each lab uses to identify DNA markers of the disease.

Preliminary research from Dr. Ren and colleagues found that this variation disproportionally affects children in racial and ethnic minority groups. Screenings across the country were less likely to detect CF in patients of color, leading to false-negatives, delayed diagnoses, and health disparities.

To reduce these disparities and identify best practices for CF newborn screenings, the Cystic Fibrosis Foundation awarded funding to Dr. Ren and colleagues at CHOP. The researchers will study the impact of changes in screening algorithms on children from racial and ethnic minorities, as well as identify barriers to early CF treatment.

Detection rates of cystic fibrosis in a U.S. population of 46,729, using a common panel that tests for 139 variants, varied by race and ethnicity. (Source: ME McGarry, et al. Pediatri Pulmonol 2022; 58:465-474)

Discrepancies in detection and early treatment

While most CF cases in the U.S. are caused by the F508del mutation, more than 2,000 variants of the cystic fibrosis transmembrane conductance regulator (CFTR) gene can cause the disease. All CF newborn screening algorithms in the U.S. incorporate DNA testing to identify variants of the CFTR gene, however, the number of mutations that each lab screens for varies widely. People of color may be affected by gene variants that differ from the common mutations found in white patients.

Moreover, state algorithms are constantly evolving, giving researchers an interesting opportunity to compare how expanding to a larger CFTR panel could affect patient outcomes. For example, New Jersey changed from screening for a single CFTR variant (F508del) to a panel of 139 variants in July 2022, and Pennsylvania moved to an algorithm utilizing next generation sequencing in October 2022.

Dr. Ren and his research team plans to compare rates of CF diagnosis by race and ethnicity in states that have recently increased the number of CF-causing gene variants in newborn screenings. The states they will be analyzing account for about 20% of U.S. births (Georgia, North Carolina, New Jersey, New York, Pennsylvania, and Wisconsin).

Data showing the impact these changes have had on CF screening disparities are essential to make screening programs more equitable, Dr. Ren said.

"Our goal is that by having these data available, we're able to provide it to the CF Foundation and other advocacy organizations that can show their states that they could be missing cases," he said.

Differences in screening algorithms are not the only barrier to equitable treatment. Studies from Dr. Ren and colleagues show that the age of first treatment is higher for Black and Hispanic children when compared to white children.

Dr. Ren said that clinicians' implicit bias may contribute to these disparities. For example, a physician may be less likely to refer a patient of color for a sweat test (the confirmatory diagnostic test for CF), since CF has historically been considered a "white" disease, even though it affects people from all racial and ethnic groups.

Beyond clinician bias, the CHOP research team will aim to identify other factors that could contribute to later in treatment in infants from racial minorities who have a positive newborn screening result. They will use state newborn screening records, zip code-level data, and data from surveys of CF Care Centers to identify the social determinants of health that might contribute to disparities in care, such as access to transportation.

"One of the great things about working here at CHOP is that we have geospatial analysts who are experts in using zipcode-based data," Dr. Ren said. "We'll collaborate with them to study delays or barriers to early treatment and evaluation."