Presumed clomiphene-induced optic neuropathy: A case report

Background: Clomiphene citrate is an estrogen receptor ligand with mixed agonistic–antagonistic properties used for the treatment of female and male infertility. Various visual disturbances and several irreversible visual outcomes have been associated with clomiphene citrate. In this report, we present a patient with presumed clomiphene-induced optic neuropathy. Case: A 33-yr-old man with acute visual loss of the right eye was referred to Amiralmomenin Hospital, Rasht, Iran in November 2018. His only medication was clomiphene citrate 100 mg daily, taken for 2 wk for fertility issues. The patient presented with a sudden decrease of visual acuity in the right eye on the 14th day of starting the treatment and subsequently developed complete loss of inferior visual field within a few days. On examination, the visual acuity was 6/20 in the right and 20/20 in the left eyes, with a right relative afferent pupillary defect and decreased red color saturation. The fundus examination revealed optic disc swelling with venous dilation in the right eye and a normal left fundus with a crowded disc (disc-at-risk). The patient was evaluated for systemic disorders, all of which were normal. Findings were suggestive of non-arteritic anterior ischemic optic neuropathy most likely due to clomiphene. Conclusion: As clomiphene may increase blood viscosity, it is hypothesized that reduced flow in a posterior ciliary artery in conjunction with the disc-at-risk contributes to the anterior ischemic optic neuropathy. It is advised that patients with disc-at-risk be aware of the possible non-arteritic anterior ischemic optic neuropathy and those experiencing visual symptoms while taking clomiphene be examined promptly for evidence of optic nerve injury. Key words: Clomiphene citrate, Optic neuropathy, Visual acuity, Ischemia.

2’, 3’, 4’-trihydroxychalcone is an Estrogen Receptor Ligand Which Modulates the Activity of 17β-estradiol

ABSTRACTMenopausal hormone therapy (MHT) reduces the risk of osteoporosis, fractures, obesity and diabetes, but long-term MHT increases risk of other diseases. Safe long-term MHT that exploits its benefits and abrogates its adverse effects requires a new approach. Here we demonstrate that 2’, 3’, 4’-trihydroxychalcone (CC7) acts as an estrogen receptor alpha (ERα) ligand that may improve the safety profile of MHT. CC7 reprograms the actions of estradiol (E2) to regulate unique genes in bone-derived U2OS cells, with 824/1358 genes not regulated by E2. The proliferative action of E2 on human MCF-7 breast cancer cells and mouse uterus is blocked when combined with CC7. Thermostability and molecular dynamics simulation studies suggest that CC7 binds concurrently with E2 in the ERα ligand binding pocket to produce a unique coliganded conformation to modulate ERα. Compounds such as CC7 that act as coligands represent a new class of ERα reprograming drugs that potentially can be combined with existing estrogens to produce a safer MHT regimen for long-term therapy.

High-Performance Prediction of Agonists on Human Estrogen Receptor Based on Chemical Structures

Many agonists for the estrogen receptor are known to disrupt endocrine functioning. We have developed a computational model that predicts agonists for the estrogen receptor ligand-binding domain in an assay system. Our model was entered into the Tox21 Data Challenge 2014, a computational toxicology competition organized by the National Center for Advancing Translational Sciences. This competition aims to find high-performance predictive models for various adverse-outcome pathways, including the estrogen receptor. Our predictive model, which is based on the random forest method, delivered the best performance in its competition category. In the current study, the predictive performance of the random forest models was improved by strictly adjusting the hyperparameters to avoid overfitting. The random forest models were optimized from 4,000 descriptors simultaneously applied to 10,000 activity assay results for the estrogen receptor ligand-binding domain, which have been measured and compiled by Tox21. At this time, our model delivers the highest predictive power on estrogen receptor agonists in the world. Furthermore, analysis of the optimized model revealed some important features of the agonists, such as the number of hydroxyl groups in the molecules.