Maternal Obesity, Cage Density, and Age Contribute to Prostate Hyperplasia in Mice. (February 2016)

• Record Type: Journal Article
• Authors: Benesh, Emily C.; Gill, Jeff; Lamb, Laura E.; Moley, Kelle H.
• Is Part Of: Reproductive sciences. Volume 23:Number 2(2016:Feb.)
• Page Start: 176
• Page End: 185
• Publication Date: 2016-02
• Subjects: prostate hyperplasia -- cage overcrowding -- maternal obesity -- developmental programming -- generalized linear modeling; Reproductive health -- Periodicals; Reproduction -- Periodicals; 612.6
• DOI: 10.1177/1933719115597767
• Languages: English
• ISSNs: 1933-7191

Abstract

Identification of modifiable risk factors is gravely needed to prevent adverse prostate health outcomes. We previously developed a murine precancer model in which exposure to maternal obesity stimulated prostate hyperplasia in offspring. Here, we used generalized linear modeling to evaluate the influence of additional environmental covariates on prostate hyperplasia. As expected from our previous work, the model revealed that aging and maternal diet-induced obesity (DIO) each correlated with prostate hyperplasia. However, prostate hyperplasia was not correlated with the length of maternal DIO. Cage density positively associated with both prostate hyperplasia and offspring body weight. Expression of the glucocorticoid receptor in prostates also positively correlated with cage density and negatively correlated with age of the animal. Together, these findings suggest that prostate tissue was adversely patterned during early life by maternal overnutrition and was susceptible to alteration by environmental factors such as cage density. Additionally, prostate hyperplasia may be acutely influenced by exposure to DIO, rather than occurring as a response to worsening obesity and comorbidities experienced by the mother. Finally, cage density correlated with both corticosteroid receptor abundance and prostate hyperplasia, suggesting that overcrowding influenced offspring prostate hyperplasia. These results emphasize the need for multivariate regression models to evaluate the influence of coordinated variables in complicated animal systems.