Understanding the dopaminergic pathway relative to men's sexual dysfunction in patients with Parkinson's disease: a narrative review with implications for future research.
Nicholas A DeebelKim ThaiRanjith RamasamyRyan P TerleckiPublished in: International journal of impotence research (2022)
Parkinson's disease (PD) is often most recognized for motor symptoms but associated non-motor symptoms such as sexual dysfunction can significantly impact quality of life. This condition involves a hormonal disruption and has a predilection for male patients, yet there are no formal guidelines for screening or management of sexual health pathology in these patients. While prior publications have addressed the presence of sexual dysfunction (SD) among men with PD, there has been a paucity of work examining the hypothalamic-pituitary-gonadal (HPG) axis and the interplay between dopamine, prolactin (PRL), and testosterone. This review provides an overview of data extracted from the existing peer-reviewed literature regarding hormonal and sexual health changes in men with PD and the impact of dopaminergic and/or androgen replacement therapy. Furthermore, while some research suggests that PD patients are at higher risk for prolactin elevation and testosterone deficiency, heterogeneity of the data limits extrapolation. Additionally, data related to pharmacologic optimization of the HPG axis in this patient population is similarly limited. Prospective studies are needed to better characterize the hormonal pathophysiology of PD as it relates to sexual dysfunction such that men at risk can be effectively identified so as to offer interventions that may improve quality of life.
Keyphrases
- end stage renal disease
- replacement therapy
- newly diagnosed
- ejection fraction
- chronic kidney disease
- oxidative stress
- mental health
- prognostic factors
- big data
- peritoneal dialysis
- systematic review
- metabolic syndrome
- middle aged
- current status
- smoking cessation
- depressive symptoms
- single cell
- machine learning
- type diabetes
- artificial intelligence