Bazedoxifene and conjugated estrogen combination maintains metabolic homeostasis and benefits liver health

Abstract

The bazedoxifene and conjugated estrogens (CE+BZA) combination has been shown to prevent visceral adiposity and weight gain after ovariectomy. However, its impact on the liver transcriptomes associated with prevention of hepatosteatosis is yet to be determined. In the present study, we use liver transcriptomics and plasma metabolomics analysis to characterize the effects of various estrogens on liver. The CE+BZA combination was very effective at preventing ovariectomy-induced weight gain in mice fed a high-fat diet (HFD). In CE+BZA treated animals, liver weight and hepatic lipid deposition were significantly lower than in Vehicle (Veh) treated animals. Additionally, CE+BZA induced unique liver transcriptome and plasma metabolome profiles compared to estradiol, conjugated estrogens alone, and bazedoxifene alone. Blood plasma metabolite analysis identified several metabolites similar to and distinct from other estrogen treatments. Integrated pathway analysis showed that gene networks that were associated with inflammation, reactive oxygen species pathway and lipid metabolism and their relevant metabolites were regulated significantly by CE+BZA treatment. Thus, long-term CE+BZA treatment modulated hepatic metabolic gene networks and their associated metabolites and improves hepatic health without stimulating the uterus.

Long-Term Administration of Conjugated Estrogen and Bazedoxifene Decreased Murine Fecal β-Glucuronidase Activity Without Impacting Overall Microbiome Community

“…Since our previous study showed CE+BZA treatment decreased serum glucuronic acid in the mice 15 , we decided to use machine learning with ERF algorithm to integrate microbiome and metabolite datasets 15 to obtain a deeper understanding how the gut microbiome impacts the metabolism of different estrogens. The ERF analysis identified liver weight, two fecal bacterial genera- Akkermansia and Anaerotruncus and several metabolites including glucuronic acid as features that could discriminate between individuals with low and high percent weight gain after ovariectomy and estrogen supplementation (Fig.…”

“…Forty female C57BL/6 J mice were housed individually in 12-h light-dark cycle. All mice were given a high-fat diet and water ad libitum at 8 weeks of age and ovariectomized at 10 weeks of age then were divided randomly into five treatment groups as described previously 15 : (1) vehicle at 43% DMSO, 15% ethanol, and 42% saline (Veh); (2) E2 at 5 µg·kg −1 ·day −1 ; (3) CE at 2.5 mg·kg −1 ·day −1 ; (4) BZA at 3 mg·kg −1 ·day −1 ; (5) CE+BZA. The high fat diet for these studies (Harlan TD.88137) is based on an AIN76A diet (45% Kcal from fat).…”

“…The very high fat diets (60% Kcal from fat) were not used to induce obesity, because we wanted to study a comparable level of fat consumed by humans in the US (~34% Kcal from fat; NHANES). We have previously used this diet to mimic the diet that humans in US consume and establish a model of low estrogen and high-fat diet associated metabolic disease in mice 13 – 15 . We selected the dosage of the estrogens based on previously published studies 9 , 10 .…”

“…In addition, the CE+BZA combination decreased serum leptin levels, leptin/adiponectin ratio, and thiobarbituric acid reactive substances in female mice, preventing fat accumulation and improved insulin resistance and glucose intolerance without stimulating uterine growth 10 . Our previous study using a well-established estrogen deficiency model 11 – 14 showed that CE+BZA treatment decreased weight gain after ovariectomy and improved liver steatosis by regulating gene expression programs associated with liver lipid metabolism 15 . In addition, we reported that serum glucuronic acid – a product of deconjugation of estrogens- levels were decreased in mice, leading to our hypothesis that CE+BZA may impact the metabolism of estrogens in the gut.…”

“…We performed substrate competition studies for the GUS activity in Escherichia coli K12 and Lactobacillus gasseri ADH using several estrogen conjugates. In addition, we used machine learning with Extended Random Forest (ERF) algorithm 25 – 27 to integrate microbiome and metabolome data from the same study 15 to identify fecal bacterial biomarkers for the effectiveness of ERT.…”