Large-scale in silico identification of drugs exerting sex-specific effects in the heart

Abstract

Background: Major differences exist between men and women in both physiology and pathophysiology. Dissecting the underlying processes and contributing mechanisms of sex differences in health and disease represents a crucial step towards precision medicine. Considering the significant differences between men and women in the response to pharmacotherapies, our aim was to develop an in silico model able to predict sex-specific drug responses in a large-scale.

Methods: For this purpose, we focused on cardiovascular effects because of their high morbidity and mortality. Our model predicted several drugs (including acebutolol and tacrine) with significant differences in the heart between men and women. To validate the sex-specific drug responses identified by our model, acebutolol was selected to lower blood pressure in spontaneous hypertensive rats (SHR), tacrine was used to assess cardiac injury in mice and metformin as control for a non-sex-specific response.

Results: As our model predicted, acebutolol exhibited a stronger decrease in heart rate and blood pressure in female than male SHRs. Tacrine lowered heart rate in male but not in female mice, induced higher plasma cTNI level and increased cardiac superoxide (DHE staining) generation in female than male mice, indicating stronger cardiac toxicity in female than male mice. To validate our model in humans, we employed two Chinese cohorts, which showed that among patients taking a beta-receptor blocker (metoprolol), women reached significantly lower diastolic blood pressure than men.

Conclusions: We conclude that our in silico model could be translated into clinical practice to predict sex-specific drug responses, thereby contributing towards a more appropriate medical care for both men and women.

Keywords: Cardiovascular drug; Precision medicine; Sex differences.

Fig. 1

The framework for an in silico prediction model of sex-biased drug responses. The in silico pipeline first identified sex-biased genes in healthy cardiac tissues from a GEO public gene expression dataset (a). Then the pipeline build associations between sex-biased genes from the GEO dataset and drug-deregulated genes from the Connectivity Map database. The drugs with significant associations with the heart sex-biased genes will be predicted to have sex-biased effects on human heart. Top 20 predictions (b)

Fig. 2

Sexual differences of therapeutic evaluation for acebutolol and tacrine on heart. a Acute administration acebutolol, the change of heart rate was assessed. Treatment SHR with acebutolol for 4 weeks, the changes of heart rate (b) and blood pressure (c) were determined. Administration tacrine for 3 weeks, the heart rate changes (d), plasma cTNI level (e) and superoxide generation of heart by DHE staining were measured in mice, and metformin as a negative control for sexual differences. All data are present as mean ± SD. *P < 0.05; **P < 0.01 between two groups