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01.12.2018 | Research | Ausgabe 1/2018 Open Access

Journal of Translational Medicine 1/2018

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

Journal of Translational Medicine > Ausgabe 1/2018
Changting Cui, Chuanbo Huang, Kejia Liu, Guoheng Xu, Jichun Yang, Yong Zhou, Yingmei Feng, Georgios Kararigas, Bin Geng, Qinghua Cui
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12967-018-1612-6) contains supplementary material, which is available to authorized users.
Changting Cui and Chuanbo Huang contributed equally to this work



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.


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.


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.


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.
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