A new test for cystic fibrosis takes just two minutes and a scrape across the forehead
Availability of better tests could lead to earlier diagnosis, which is crucial for effective management of the disease
Cystic fibrosis (CF) is a chronic condition which primarily affects the lungs and digestive system. A new study published in PNAS presents a new diagnostic method — the test takes just two minutes, is minimally invasive, requires no sample processing, and is highly accurate.
Every individual has two copies of the CFTR gene. In order to present with CF, both copies of the CFTR gene will contain mutations, resulting in a non-functional protein. Dysfunctional CFTR leads to a mucus build-up, resulting in persistent lung infections and other organ complications.
While there is currently no cure for CF, an early diagnosis means that therapies, like antibiotics to prevent lung infections and mucus-thinning drugs, can be started earlier, improving an individual's quality of life and increasing life expectancy. Currently, a sweat chloride test is the gold standard for CF diagnosis; this test measures the amount of chloride (a component of salt) that is present in sweat.
First described in 1959, in this test, a colorless chemical and a small pulse of electrical simulation is applied to a small area of skin, over a five minute period, to prompt sweating. This sweat is then collected using filter paper or gauze for about half an hour, before being sent off to a laboratory for chloride analysis. This entire test can take up to three hours to complete. This test is also prone to technical errors, and requires a high degree of skill, especially when it comes to testing newborn children.
In this new study, researchers have developed a two minute test to diagnose CF. It involves gently swiping a standard microscope slide across an individual’s forehead to collect sweat products, instead of stimulating sweat. This five second scrape needs no additional sample processing — mass spectrometry can be directly applied to the microscope slide to analyze the sweat components, taking a total of two minutes to collect and test samples. Coupled with a machine learning algorithm, the researchers were able to correctly identify CF cases 98% of the time (with a 2% margin of error).
While this is simply a proof-of-concept, the study offers the potential of earlier, and less invasive, CF diagnosis. Will it replace the the sweat chloride test and become the gold standard for CF diagnosis? Only time — and additional testing — will tell.