AI Article Synopsis

  • Drug-induced long QT syndrome (diLQTS) is a serious side effect of over 150 medications that can lead to dangerous heart conditions; the study aimed to validate a genetic risk score for predicting this syndrome.
  • Researchers analyzed data from a large cohort of patients taking high-risk QT-prolonging drugs and found that the risk score was significantly associated with diLQTS in White patients, indicating a higher likelihood of QT prolongation during treatment.
  • Although the risk score showed promise in identifying high-risk individuals, the study was underpowered to confirm its effectiveness across African American and Asian populations, highlighting the need for larger sample sizes in diverse groups.

Article Abstract

Objective: Drug-induced long QT syndrome (diLQTS) is an adverse reaction from over 150 FDA-approved medications, posing the risk of triggering torsades de pointes and sudden death. While common genetic variants may modestly impact QT interval individually, their collective effect can significantly amplify risk of diLQTS. Consequently, this study aimed to validate a polygenic risk score (PRS) for diLQTS previously proposed by Strauss et al .

Methods: A retrospective cohort study was conducted utilizing patients from the Michigan Genomics Initiative prescribed 27 high-risk QT-prolonging drugs and an ECG during the prescription. The primary outcome was marked prolongation of the QTc interval (either >60 ms change from baseline or >500 ms absolute value) during treatment with a high-risk QT-prolonging drug.

Results: The primary outcome occurred in 12.0% of n  = 6070 self-reported White, 12.4% of 558 African American, and 8.2% of 110 Asian patients. The PRS significantly associated with diLQTS in White patients [adjusted odds ratio = 1.44 (95% CI: 1.09-1.89); P  = 0.009]. However the study lacked sufficient statistical power to confirm the PRS as a risk factor in African Americans [adjusted odds ratio = 2.18 (95% CI: 0.98-5.49); P  = 0.073] and Asians [adjusted odds ratio = 3.21 (95% CI: 0.69-16.87); P  = 0.139] due to smaller sample sizes in these groups.

Conclusion: The previously published PRS for diLQTS was validated in a large, real-world cohort, demonstrating its potential as a tool for identifying high-risk patients. Incorporating this PRS into routine clinical practice could enable proactive measures to prevent life-threatening diLQTS.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543509PMC
http://dx.doi.org/10.1097/FPC.0000000000000548DOI Listing

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