Inhalers seem to be increasingly common around elementary school playgrounds. The National Center for Environmental Health confirms this apparent trend, noting that both incidents of asthma and asthma-related fatalities have increased in recent decades. Asthma affects 7 million children and leads to 3,000 deaths a year, yet there is still no cure. Michael Bracken, Professor of Epidemiology at the Yale School of Public Health, and his team aim to curb these statistics.
Bracken served as the principal investigator for a study known as the Perinatal Risk of Asthma in Infants of Asthmatic Mothers (PRAM). The study involved recruiting asthmatic and non-asthmatic pregnant women, and then testing their children for similar asthma markers. Due to the need for a genetic analyst, Andrew DeWan, Assistant Professor of Epidemiology, was brought onto the team for his expertise.
In order to identify multiple high-interest genes, the team decided to use three different analytical methods for the same sample population, the first of these being a genome-wide association study. This technique scanned the entire genome of 66 asthmatic children and 42 non-asthmatic subjects. This genome study was useful, as the team initially had no specific gene in mind. Surprisingly enough, the data revealed a cluster of variants in the PDE11A gene, indicating that this gene was in some way related to asthma. This association remained even after increasing the sample size. Armed with a specific gene, the team was then able to refer to other genome studies and inquire whether other scientists could find a similar relationship between asthma and variants in the PDE11A gene. This association was confirmed in three other studies.
The second technique involved a candidate-gene approach. Graduate student William Murk conducted a literature review of several hundred papers relating to asthmatic genes, from which he compiled a list of 251 candidates. The team then ranked each of these genes using an algorithm that combined information from the literature search and the genome-wide association study. Upon genotyping the top genes in additional asthmatic and non-asthmatic children, one gene in particular, RAD50, had a distinct and promising association.
The team’s final analytical test looked at a specific genetic mutation, known as a copy number variation (CNV). A CNV is an amplification or deletion of a large genome segment. The scientists observed a trend of deletions at the T-cell receptor gamma locus, a gene that had already been associated with asthma. In remarks to this interesting phenomenon surrounding these deletions, the team’s geneticist DeWan explains, “Normally if the segment was deleted in all the cells, you would either see one copy or zero copies because every locus exists as two copies in every cell – but we only saw a reduction, not zero or one.” This would indicate that the mutation was not inherited but acquired during the individual’s lifetime. This conclusion was confirmed by noting that the parents’ genomes did not contain this mutation.
These findings may be important in trying to analyze what proportion of asthmatic susceptibility can be attributed to either genetic factors or perinatal environment. Though more analysis must be done with the compiled genetic data, the team hypothesizes that a combination of these genetic markers, as well as environmental factors such as the perinatal environment, will be able to determine where a person would fall on the asthmatic spectrum, a key step towards fully understanding the process of developing asthma.