Historically, medical studies have consistently excluded female participants. Instead, research data has been predominantly collected from male participants, and generalized to female patients — often with negative health outcomes. According to a 2022 survey of medical literature exploring sex inequalities in medical research, “women wait longer than men for both a diagnosis and pain relief, and are more likely to be misdiagnosed or discharged during serious medical events.”

Ongoing research at Miami University’s College of Engineering and Computing (CEC), led by professor Justin Saul and currently supported by a $2.5 million multi-year National Institutes of Health (NIH) grant, places women’s health (specifically osteoporosis in women) as its primary focus. According to the project details of this research, approximately 40 million women have, or are at risk of developing, osteoporosis. Not only that, the majority (approximately 60%) of the two million osteoporotic bone fractures which occur each year, occur in women. Saul’s research aims to utilize cell-based, tissue-engineered ovarian constructs as a treatment for osteoporosis in women specifically. However, the implications of this research are hypothesized to more broadly support women’s health in a number of different ways, including cardiovascular health.

The project, “Sustained regulation of hypothalamus-pituitary-ovary hormones with tissue-engineered ovarian constructs as a treatment for osteoporosis in females,” is led by Saul, a professor of Chemical, Paper, and Biomedical Engineering at Miami University, and strengthened by a team of Co-Principal Investigators and Co-Investigators with deep expertise across disciplines. This includes co-Principal Investigators Emmanuel Opara of Wake Forest University Health Sciences, Saami Yazdani of Wake Forest University, and Barbara Boyan of Virginia Commonwealth University. Along with this expertise in health sciences, the project is also supported by thought leaders in statistics and bioinformatics: Michael O'Connell, assistant professor of Statistics at Miami University, Andor Kiss, director of the Center for Bioinformatics and Functional Genomics at Miami University, and Byran Smucker, senior scientist at Henry Ford Health in Detroit.

We recently caught up with Saul for a Q&A on his project, ongoing hypotheses, and their corresponding health implications for women.

Historically, we know much more medical research has been done regarding the functionality of men’s bodies vs. women’s bodies. Is that something that you and your team think about or talk about as you progress in your research?

Absolutely. There are new treatment modalities that are needed. You can't go to a traditional physiology textbook that's geared around a 75 kilogram adult male and deal with some of these issues. This grant's going to look at that in an important way. 

Why does the loss of ovarian function lead to osteoporosis in women? 

There's a couple of answers to that. One is what people refer to as the estrogen protection effect. Once you see loss of ovarian function, whether that's through menopause, cancer ablative therapy, or some sort of genetic condition, you're going to lose your primary source of estrogen production. So there are other places in the body that'll produce estrogen, but in females, the ovaries are the primary source for the estrogen. So when those estrogen levels drop, they're not able to interact with estrogen receptors in cells throughout the body, including bones. When you lose the estrogen, you decrease the amount of bone formation that you get, and you increase the amount of bone resorption. You end up with an osteoporotic phenotype in bone, which can mean more brittle bones. You see hip fractures, you see wrist fractures. You'll see vertebral collapse and things like that because the bones are more porous. 

How can a loss of ovarian function, and its corresponding dip in estrogen production, impact other areas of women’s health?

Estrogen acts directly on estrogen receptors throughout the body — including bone —  but it has other effects on other hormones that then could have secondary effects on bone and other tissues. Some estrogen receptors are in the brain. So a drop in estrogen levels can impact those receptors and lead to things like vasomotor effects, or what people call hot flashes. There are also estrogen receptors in cardiovascular tissue. 

How does your research address these issues?

Right now, we're treating the cardiovascular aspects as a safety outcome. So if you want to think of it as a safety and efficacy type of study, the efficacy that we're looking at is bone health. We're looking at the bone tissue. We'll take micro-computed tomography images. We'll do some analysis to see if we're reducing the amount of osteoporosis. That's on the efficacy side.

On the safety side, we're taking heart tissue and we're looking to see if there's any evidence of changes in the way that the heart tissue remodels in response to not having ovarian function. With drug-based therapies, there's evidence in the literature that there is a kind of remodeling in the heart tissue. What we want to look at is: Are the changes that happen in cardiovascular tissues when you use a drug-based hormone therapy there to as great of an extent when you use a cell-based therapy like the one we’re developing? Our hypothesis is that the cell-based therapy that we're developing might ultimately lead to better cardiovascular outcomes, reduce the risk of stroke, or at least reduce the remodeling that you see in the cardiovascular tissue after loss of ovarian function.

Is loss of ovarian function an inevitability for women as they age?

We know that at some point in a female's life, if she lives long enough, she's going to run out of follicles, and that leads to all the changes that lead to the loss of estrogen production. So, yes, at some point women are going to lose that ovarian function. But part of what we're thinking with our research area is we're kind of trying to make it not inevitable. Effectively, we're making an artificial ovary — with the exception that the artificial ovary that we're making would not be useful for reproductive purposes. Our goal with what we're doing is that we could implant these artificial ovaries and at least have a regulation of circulating hormone levels that would be somewhat similar to the way that things operated before the woman went through menopause.

Mathematical models and statistics seem to feature heavily in your work. Why is that?

A lot of this research is biological in nature.  We're taking measurements and we're trying to figure out if there's a difference between our cell-based treatment, another treatment like a drug-based therapy, or no treatment. Anytime you're taking those types of measurements, statistics is really important.  

Part of putting together the team we have was getting a couple statisticians on board so that they could help us design our experiments properly and have proper controls, and then also be able to determine if there are actually statistical differences between these things. They're helping us try to understand whether things that we see are statistically meaningful or not.

In terms of mathematical modeling, there have been a lot of questions around, “Are your artificial ovaries really acting like normal ovaries?” Because there are some differences, like you don't have cell proliferation the way that you do in the native ovary. Which leads to the question, “Are you sure that these constructs are actually participating in that endocrine system?” and “Are you sure that these cell-based constructs are really participating in the endocrine system feedback loop, or are they just acting the same way that drug-based therapies do?”

Part of the rationale for doing some of the mathematical modeling work originally was to take the data that we've already collected and to see if we take known interactions  – between the hypothalamus, the pituitary, and the ovary – and see if the data validates that some of these known interactions are actually happening with our cell-based constructs. We feel like that mathematical model is going to be something that we can come back and revisit to kind of further understand how the constructs are working. Hopefully it can help us understand some of the biological results that we see in the future.

Are there any milestones that you feel comfortable sharing at this point of your research?

What I can say is we have some pretty exciting results about how long this approach can work. We're seeing effects that last longer than what we've previously reported, so that's pretty exciting to us.