Jing Cui, PhD: SLE Risk Assessment Among Nurse Cohorts

November 6, 2021
Giuliana Grossi

Dr. Jing Cui speaks about how she examined lifestyle and environmental factors as well as genetic risk to assess risk of systemic lupus erythematosus.

In this interview, Jing Cui, PhD, Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, spoke about her study that's being presented at the American College of Rheumatology 2021 Convergence.

The study is titled "Risk Prediction Models for Incident Systemic Lupus Erythematosus using Lifestyle/Environmental Risk Factors and a Genetic Risk Score".

Cui explained that this study examined 2 cohorts of nurses called the Nurses' Health Studies. The first one began in 1976 and enrolled 121,700 registered female nurses aged 30-55, the second started in 1989 and enrolled 116,430 registered female nurses aged 25-42.

Because this research focused on a population of nurses, Cui noted that they may have a tendency to display healthier lifestyles than the general population. She explained that in other research, smoking has been a prominent risk factor for systemic lupus erythematosus but wasn't prevalent in this model.

Within this model, investigators found that the weighted genetic risk scores (wGRS), obesity, and a young age of menarche (less than 10 years) were the most impactful factors.

Another thing that Cui pointed out was that this population had a majority of white females. This is something to take into consideration when evaluating the results because other research has shown disparities in racial groups when it comes to systemic lupus erythematosus risk and prevalence, especially in the African American population.

The investigators are interested in validating their prediction model in a more diverse cohort.

There are many aspects to understand when it comes to systemic lupus erythematosus risk. Cui said that the next step would be to explore other environmental factors, such as family history, air pollution, sleep, and maybe even gene environmental interactions.


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