Data Analysis Reveals Genes Linked to Rare Respiratory Disease
An extensive data analysis screening for genetic sequences found a rare respiratory disease was more common than initially believed.
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By - According to a large data analysis by the Indiana University School of Medicine, the rare respiratory disease called primary ciliary dyskinesia (PCD) is more common than previously thought.
The data analysis aimed to understand the global prevalence and genetic variance of PCD, a genetic condition that impacts the protective function of the respiratory system. PCD can lead to chronic health issues, such as chronic coughing and congestion, recurring respiratory and ear infections, and severe lung damage.
Using information from two databases, researchers screened the genetic sequences of 180,000 individuals for disease-causing variants of 29 genes linked to autosomal recessive PDC.
While PDC was previously estimated to occur in about 1 in 16,000 people, the data analysis revealed that disease is twice as common, occurring in about 1 in 7,500 individuals.
“This is very important for clinicians. Since PCD has been thought of as a rare disease, they might not recognize it when they see a patient with PCD symptoms,” study leader and Indiana University School of Medicine professor, Benjamin Gaston, said in a press release.
“They may think, ‘Well, it’s unlikely because it’s such a rare disease.’ But actually, it’s not anywhere near as rare as we thought.”
The team studied the disease prevalence among seven ethnic groups, finding that those of African descent have higher rates of PCD-causing variants than any other population.
Additionally, the data showed that of the 29 genes studied, the five most common genes with PCD-causing variants were different in different ethnic groups. According to the researchers, the data can assist doctors in recognizing and diagnosing PCD in patients, especially when treating patients from diverse backgrounds.
“My hope is that clinicians will have a much lower threshold for evaluating people who might have PCD,” said Gaston.
Using this type of large-scale analysis to identify disease prevalence is a growing approach in scientific discovery. However, it is not the first time Gaston applied discoveries from his lad to large quantities of genetic data.
According to Gaston, he hopes that researchers continue to discover new genes associated with PCD to continue improving diagnosis and care for people with PCD.
For this study, the group used a California-based genetics laboratory, Invitae, and an international sequence database called Genome Aggregation Database (gnomAD).
