Based on DNA from nasal cells taken with a nasal swab, allergies can be revealed using the new algorithm. It is sufficient to see only three places in the DNA for this. This new algorithm was developed during research by UMCG, the Medical University of Hannover (MHH) and the artificial intelligence (AI) firm MIcompany. As described in a publication in Nature Communications, this research contributes to a better understanding of these complex diseases. This will also provide opportunities for innovative diagnostics in the future.
Allergies burden the quality of life
Over the past 50 years, the number of patients with allergic diseases has increased rapidly. So strong that researchers even expect that half of the European population will suffer from it by 2030. This means that conditions such as asthma, eczema or hay fever, as very common childhood diseases, put a significant burden on the quality of life of patients and the healthcare system.
Although genetic and environmental factors are known to play a major role in its development, the precise mechanisms that contribute to this are still unknown. This fact ensures that there is currently no permanent cure for a chronic disease.
Diagnosing allergies in young children
The need for a prediction of the risk of allergic diseases is particularly great for young children who have not yet started school. However, it is especially difficult to determine in children. Or as Prof. Gerard Koppelman, pediatric pulmonologist at UMCG and initiator of the project, says: “Small children often suffer from short-term ailments where the symptoms can resemble an allergic condition, such as shortness of breath or frequent colds. It is therefore difficult to diagnose a chronic allergic disease.” An algorithm provides additional insight to arrive at a better diagnosis.
Three DNA markers in nasal cells
The amount of knowledge about human DNA has doubled every seven months in the past decade. Knowledge that provides many new insights into diseases. For example, GRIAC (Groningen Research Institute for Asthma and COPD) has DNA data from blood and nasal cells from participants in the national birth cohort.
By analyzing DNA data on a large scale, the researchers found three DNA markers in nasal cells that determine the development of an allergic patient. They were able to demonstrate that these three DNA markers are associated with an inflammatory reaction in nasal cells. From three DNA markers, the new algorithm can calculate a risk score for an allergic disease and use it to make a diagnosis.
Blood test versus nasal swab
As mentioned, several methods have often been used to diagnose an allergic disease in children. In the case of asthma, for example, a lung function test is usually carried out, which is often not yet possible in younger children (up to six years). This allows a doctor to make the diagnosis based on certain symptoms, such as shortness of breath and a wheezing sound when breathing.
When it comes to diagnosing hay fever, in addition to looking at known symptoms such as a cold and runny nose, a blood test or a skin test is also done. Such a blood test is especially annoying for small children. Koppelman therefore wants to make diagnosing children more friendly and efficient by developing a nasal swab test based on the three DNA markers identified in the current study.
The new algorithm has also been found to be very useful in diagnosing children outside of Europe. This indicates that the algorithm is indeed capturing common biological signals present in other ethnic groups. This external review is the gold standard in medical research to test whether results are reliable.
The current algorithm was developed for 16-year-olds. “Although this discovery is an important step forward in the application of artificial intelligence to diagnose allergies, we need to adapt our algorithm to the younger age group in the future,” continues Koppelman. In the future, he will use the algorithm to diagnose allergies in young children using a nasal swab.
AI in complex disorders
In 2019, UMCG and MIcompany joined forces to conduct research applying the latest artificial intelligence techniques to complex biomedical problems. At the initiative of Gerard Koppelman and Marnix Bügel (founding partner MIcompany), the new algorithm was developed by a joint research team as part of this collaboration.
The key to the success of this study was the combination of expertise. Artificial intelligence enables researchers to analyze large and complex data sets in a new way. The resulting data is essential to reach meaningful conclusions.
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