The following is a transcript of an interview with Rachel Zsido, PhD student at the Max Planck Institute for Human Cognitive and Brain Science, currently studying sex hormones and how they influence brain structure, cognitive health and depression susceptibility.

Hi Rachel! Can you tell us a bit about yourself and your research interests?

My background is in neuroscience. I’m interested in how ovarian hormones and other biological factors interact to influence the brain, and what implications those interactions have for cognitive health and emotional wellbeing.

One of the studies I’m working on is ‘menstrual cycle plasticity’ . We’re looking at how subtle fluctuations in hormones across the menstrual cycle influence brain plasticity –  specifically structural brain plasticity. We have women come in six times over the course of their menstrual cycle to assess how cycle-related fluctuations in hormones relate to brain volume, focusing on brain regions involved in emotion and cognitive processes.

We also have a premenstrual dysphoric disorder (PMDD) project, where we look at how ovarian hormones influence the serotonergic system across the menstrual cycle in PMDD patients. For context: we know that 800 million people menstruate daily, of which roughly 75% of them will experience premenstrual symptoms. Roughly 8% of menstruating women will experience the more severe form, PMDD, which is characterized by severe symptoms of anxiety, depressed mood, mood swings and irritability.

As the symptoms occur exclusively in the late luteal phase right before menstruation, and only during ovulatory cycles where we have these fluctuations in hormones, the immediate thought might be that there is a hormonal difference in these women. But a decent amount of research has shown that there’s no difference in absolute levels of hormones in women with and without PMDD.

So it seems that, although hormones are clearly involved, women suffering from PMDD have a sensitivity to normal cyclical, hormonal changes rather than abnormal hormone levels. That’s why PMDD is now discussed as a reproductive subtype of depression. It’s not the same as major depressive disorder. The symptoms may overlap but are not the same – the most important aspect being that the symptoms are phase-locked.

From a clinical perspective, we do know that antidepressants that slow the reuptake of serotonin, such as selective serotonin reuptake inhibitors (SSRIs), vastly improve symptoms within hours to days for patients with PMDD, compared to patients with major depressive disorder or anxiety disorder where antidepressants typically take two to three weeks to alleviate symptoms. That, alongside the important role of serotonin in mood regulation, suggests that PMDD symptoms may be driven by a hormone-induced change in serotonergic function – this is what we’re looking into.

And the last study examines inflammatory and immune marker patterns across the menstrual cycle to look at the cyclical nature of female immunity, which could have really important implications for healthcare. If you know how inflammatory patterns vary cyclically, maybe medical intervention timing could be optimized by cycle phase, especially when treating inflammation-related disorders. Maybe a better understanding of menstrual cycle regulation of the immune system could inform your decision of when to make a vaccination appointment. And perhaps more related to my field, if your menstrual cycle information can be used to calculate inflammatory load over the lifetime, this could influence the way we think about brain aging and risk trajectories over the female lifespan.

How do you see FemTech intersecting with research?

I love that FemTech not only focuses on new software and technologies for improving women’s healthcare but is also providing ways to close the data gap – we’re finally collecting datasets that address uniquely female experiences, such as the menstrual cycle, postpartum, and menopause transition. FemTech is simultaneously improving healthcare standards for women as well as advancing research on people typically excluded from studies.

Neuroscience is notably guilty of this systematic bias, with the male brain often implicitly treated as the default model. As I study susceptibility and resilience to depression, cognitive decline and dementia, this still shocks me. We know that women make up 2/3 of Alzheimer’s disease patients and are twice as likely to suffer from a depressive illness. So the population that is at greatest risk for these disorders is actually understudied, and we’re not talking about a small group of individuals – we’re talking about over half the world’s population. I think FemTech and research can intersect by combining interactive digital health technology and personalized healthcare options with neuroscience and clinical research to determine neuropsychiatric and neurodegenerative disease risk over the female lifespan, and then to optimize medical intervention timing and development.

Do you have an example of how FemTech could be used to improve healthcare?

For PMDD, aside from a medical history and psychological interviews, there are currently very few diagnostic tests and treatment options. A lot of women use birth control or antidepressants to help with PMDD symptoms. But these may not be ideal options for many women, given that symptoms only occur a few days out of the month, and these medications are really designed to be taken chronically. FemTech is already helping by providing better ways to track your menstrual cycle and record any related changes in mood and body. By tracking your cycle, you start to see the patterns, you gain control, you may be able to predict upcoming changes in mood, and you can almost ‘biohack’ the menstrual cycle. It’s just more data! You can walk into your doctor’s office and show them data.

Also our hormones are so much more than just our reproductive organs! Hormones influence the brain, our mood, our cognition, cardiovascular health… the list goes on. I think FemTech has the capacity to connect our reproductive health to full body health. So beyond developing medical intervention on a largescale, I love the idea that, by integrating in an individual’s own data, you can create personalized programs for improving one’s own health.

FemTech could also be used to leverage information from one hormonal transition period to inform later hormonal transition periods in life. Back to the PMDD example that we’ve talked about earlier – studies have shown that you have an increased risk of experiencing postpartum depression if you experienced PMDD earlier in life. So this sensitivity to the drop in hormones that occurs at the end of the menstrual cycle might be informative for more pronounced shifts in hormones later in life, such as during the postpartum period or perimenopause.

If you think about that in terms of synergies with FemTech, it could be particularly powerful if we developed technologies to build longitudinal datasets for monitoring reproductive health measures over the lifespan, to be used to better understand potential risks trajectories for brain health or whatever you’re interested in. It could inform preventative care and prepare women for upcoming changes in the body and brain in a proactive, de-stigmatizing fashion.

I’m really interested in brain aging in particular – because brain aging is the result of little steps that you take across your whole lifespan. If we could develop a tool that would allow you to conveniently record and assess the impact of all these little steps on your brain – in the context of accessible reproductive health measures – I think that would be really interesting.

 

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