Preventing Mental Illness Across the Lifespan: Meet the Team that’s getting it DUNN

The following is a guest blog post written by researchers in the Dunn Lab at Massachusetts General Hospital.

Depression is the third leading cause of disability worldwide and is projected to be the leading cause by 2030. Meet Dr. Erin Dunn and her research team, who are dedicated to reducing the burden of depression and other brain health disorders by discovering innovative approaches to prevention.

Erin Dunn, ScD, MPH, and her research team have a straightforward but ambitious goal: to prevent depression before it ever even begins. This is a critical goal to achieve because:

• Depression is common, affecting about one out of every five people worldwide;
• Depression is often difficult to treat once it emerges, making it costly to individuals, families, and society (yearly economic burden estimated at $210.5 billion); and
• Depression increases risk for other adverse events, spanning suicide to cardiovascular disease.

Yet, little is currently known about who is most at risk of developing depression. In fact, outside of asking about family history, there are currently no gold-standard tools that clinicians can use to measure a person’s risk of developing depression in the future. 

There are also no tools that can reliably measure a person’s exposure to early life trauma and adversity, which account for 30% of all depression cases.

Without such measurement tools, scientists and clinicians are unable to develop and efficiently deploy interventions to prevent a first episode of depression among people who are most at-risk.

Breakthrough scientific discoveries are urgently needed to identify such risk identification tools to guide depression prevention programming, which is now recognized as the “new holy grail of treating mental illness.” In fact, given the burden of depression worldwide, we think that identifying tools to measure future risk for depression may be one of the most important medical challenges of our time.

There are a number of things the Dunn Lab doing to make progress in this area.

• Identifying individuals most at risk for depression. Experts have known for decades that exposure to stress is one of the biggest risk factors for depression. However, not everyone who experiences stress or adversity goes on to experience mental health problems. Additionally, we don’t yet know which individuals might be more at risk for developing depression following a stressful event. Given that depression is known to be partially genetically determined, we are studying the role of both genes and life experiences in shaping risk for depression, by asking which genes confer an increased susceptibility to depression in the context of stress. We are also exploring the genomic predictors of depressive symptoms from childhood to adolescence. Finally, recognizing that non-European populations are dramatically underrepresented in genetics research, we are also working to complete genetic association studies with more diverse racial/ethnic samples. 

• Understanding how stress gets biologically embedded. Although we know that people are more likely to develop depression after experiencing a stressor, we don’t yet know how stress “gets under the skin”, or causes biological changes that increase risk for depression. We’re working to understand the mechanisms linking stress to depression risk by identifying biomarkers that shape how genes are expressed. Our work in this area is exploring how early exposure to stressors—including poverty, maltreatment, and other adversities—can leave epigenetic marks that can increase risk for depression. Understanding the biological pathways connecting stress to depression can help us better understand the causes of depression and therefore focus our interventions on potentially modifiable biological targets.

• Determining sensitive periods in development, or periods of heightened plasticity. There is a growing body of evidence suggesting that the impact of certain exposures on mental health outcomes might also depend on whether those exposures occur during “sensitive periods” in development. Sensitive periods are high-risk/high-reward stages when the brain is highly impressionable and when experiences can have lasting impacts on brain health. Using large-scale datasets, we’re working to identify when these sensitive periods occur and how they shape risk across social-emotional skills, biological processes, and risk for depression. We are also actively exploring the use of teeth and other tissue types as biomarkers of past stress exposure, the timing of those exposures, and future mental health risk. Teeth are a promising new tool for identifying sensitive periods because they preserve a kind of “fossil record” of their growth and disruptions to that growth, like rings in a tree marking its age.  After determining when these sensitive periods occur, our ultimate goal is to design interventions that not only promote brain health, but are also uniquely timed to minimize the consequences of stress and prevent depression years before it begins.

To achieve our goal of preventing depression before it begins, we routinely collaborate with scientists across several disciplines, spanning epidemiology, genetics, epigenetics, dentistry, anthropology, pediatrics, and developmental neuroscience.  This is because we have learned that interdisciplinary collaboration can lead to breakthrough discoveries. 

To date, our work has been supported by the National Institute of Mental Health, One Mind, the Brain & Behavior Research Foundation, the Russell Sage Foundation, the Robert Wood Johnson Foundation, the Jacobs Foundation, and Harvard University.

For more information about The Dunn Lab, our current initiatives, open positions, and to read our weekly blog, check out our website.

About the Mass General Research Institute
Research at Massachusetts General Hospital is interwoven through more than 30 different departments, centers and institutes. Our research includes fundamental, lab-based science; clinical trials to test new drugs, devices and diagnostic tools; and community and population-based research to improve health outcomes across populations and eliminate disparities in care.
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