Genetic data may improve prediction of steroid adverse effects

Clinical Takeaway: Genetic information may eventually help identify patients at greatest risk for corticosteroid-related complications, allowing earlier consideration of steroid-sparing therapies and closer monitoring during long-term treatment.

Oral corticosteroids remain a cornerstone of treatment for many inflammatory and autoimmune conditions, but their use is often limited by adverse effects such as osteoporosis, cataracts, and cardiovascular complications. Clinicians currently have few tools to predict which patients are most likely to experience these complications.

Researchers analyzed data from nearly 38,000 UK Biobank participants who'd received oral corticosteroids to determine whether genetic factors could improve prediction of treatment-related adverse effects. They found a clear dose-response relationship, with higher cumulative steroid exposure associated with a greater risk of side effects.

Several genetic variants were associated with specific complications. Variants in CYP3A4, a gene involved in steroid metabolism, were linked to osteoporosis risk, while variants in CTLA4 were associated with stroke and cataracts.

The most notable finding was that adding polygenic risk scores for osteoporosis improved risk prediction beyond routinely available clinical factors such as age and sex. The improvement was particularly pronounced in younger patients at the time of their first steroid prescription.

The findings may have implications for patients who require repeated or long-term corticosteroid therapy, where balancing treatment benefits against toxicity remains a common challenge. Genetic risk assessment could eventually help identify patients who may benefit from earlier use of steroid-sparing therapies, more aggressive bone protection strategies, or closer surveillance for treatment-related complications.

The researchers emphasized that the findings require validation in larger and more diverse populations before routine clinical implementation. However, the study adds to growing evidence that genomic information may help personalize prescribing decisions and improve risk stratification for commonly used medications.

“While single variants had a relatively limited influence on the risk of serious side effects from steroids, adding polygenic risk scores for traits such as bone mineral density improved risk prediction,” said lead author Deniz Turkmen, PhD. “We hope that, in time, greater availability of genetic data at population level will mean that it will be possible to integrate genomics into everyday healthcare and hence into prescribing decisions.”

Source: Turkmen D, et al. 2026 June 13. European Society of Human Genetics Conference. Adding genetic data to steroid prescribing can help predict side effects