Findings from a recent study indicated that patients with higher genetic susceptibility and poor sleep patterns have an even greater risk of developing asthma, while risks were lower in individuals with healthy sleep patterns.

In a recent publication in BMJ Open Respiratory Research, researchers conducted a large-scale, prospective study to ascertain correlations between a combination of sleep traits (healthy sleep scores) and the risk of asthma. The researchers also investigated the combined effects of sleep patterns and genetic susceptibility on the risk of asthma and examined if adherence to a healthy sleep pattern could lessen the adverse effects of genetic susceptibility to asthma.

The UK Biobank cohort involved 455,405 participants aged between 38 and 73 years (average age 56.54 ± 8.07 years). Of those, 17,836 individuals were diagnosed with asthma during an 8.1-year median follow-up period.

The researchers employed a questionnaire to examine sleep patterns using data on the following: chronotype, sleep duration each night, the incidence of insomnia, snoring, and incidence of excessive daytime sleepiness. They also evaluated a weighted polygenic risk score (PRS), which divided participants into three groups: low genetic risk, intermediate genetic risk, or high genetic risk for asthma.

The researchers employed a multivariable Cox proportional hazards regression model to explore the independent and combined effects of sleep patterns and genetic susceptibility with regard to the incidence of asthma. They also conducted a subgroup analysis across gender and sensitivity analysis, which also included a 5-year lag, diverse covariate adjustments, and repeat measurements.

The results revealed that compared with the low-risk group, individuals classified as having high genetic risk had a hazard ratio [HR] of 1.47 (95% CI; 1.41-1.52, P <.001), and patients with poor sleep patterns had a 1.55 HR (95% CI; 1.45-1.65, P <.001) for asthma.

With regard to patients with both genetic risk and poor sleep patterns, there was a 122% heightened risk for asthma compared with those with healthy sleep patterns and low genetic risk.

Among those classified as having high genetic risk who had healthy sleep patterns, there was a marginally lesser risk for asthma compared with those patients with poor sleep patterns and low genetic risk. Additionally, those with healthy sleep patterns had a decreased risk for asthma by 44%, 41%, and 37% in the groups designated as low genetic risk, intermediate genetic risk, and high genetic risk, respectively. The authors indicated that regardless of the level of genetic risk, their findings imply that establishing healthy sleep patterns could substantially reduce asthma risk in patients.

When the researchers collapsed the genetic risk categories to compare low risk versus high risk, patients with healthy sleep patterns and low genetic risk had a 25% lower asthma risk than others.

The results also indicated that each factor measured in sleep patterns was independently linked with decreases in risk for asthma, including 7 to 9 hours of sleep each day (20%), a lack of self-reported snoring (9%), early chronotype (8%), never or rare insomnia (25%), and an absence of regular daytime sleepiness (15%).

Patients with healthy scores for each of these factors had a 22% lower risk for asthma than other patients, and population attributable risk percent indicated low genetic risk and combined healthy sleep patterns would hypothetically diminish 17.26% and 19.03% of asthma cases in the population, respectively.

The authors concluded, “This large prospective study indicates that individuals with poor sleep patterns and higher genetic susceptibility have an additive higher asthma risk. A healthy sleep pattern was beneficial in asthma prevention regardless of the genetic conditions. Early detection and management of sleep disorders could be beneficial to reduce asthma incidence.”

The authors also added that their findings reveal that a poor sleep pattern may suggest a greater risk of asthma, which could be a valuable biomarker for clinicians to use in monitoring patients.

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