To Heal Depression, We Have to Learn More About the Brain

William Z. Potter, M.D., Ph.D., National Institutes of Health

Care for Your Mind acknowledges and appreciates the collaboration of the American Brain Coalition and the National Network of Depression Centers in developing this series.

With 350 million people worldwide suffering from depression and diagnoses rising steadily since the 1980s, you’d hope scientists would have a thorough understanding of this pervasive condition. Needless to say, we don’t. Not even close.

Despite decades of study, we’re just starting to scratch the surface when it comes to understanding the brain. Its complexity has proved a huge hurdle when it comes to developing effective new treatments for the millions of people dealing with depression.

Even though we’ve spent billions of dollars on mental health research, we’re still pretty clueless about how best to deal with problems localized in the brain. Two decades of effort have made progress but without nearly the level of breakthroughs we’d hoped for. While many people believe that more money is the answer, it’s not simply a question of funding that’s needed to insure progress, it’s the many other factors required to advance knowledge.

Thus, before we can make a significant breakthrough in depression treatment, we need to know more about the brain.

How the brain has stumped us
As the body’s most critical organ, the brain regulates far more processes than we can count. When it’s not working correctly, there are thousands of potential causes, and we have no way (yet) of identifying what those are. It’s not like a broken bone or an infectious organism; with the brain, there are many, many mysteries.

Depression is a particularly challenging brain condition. It affects people of all ages, backgrounds, and socioeconomic conditions and, unlike so many other illnesses, has no objective measures. Doctors can’t do a blood test or urinalysis for diagnosis. Instead, they have to rely exclusively on patients to report symptoms.

Given how much we rely on patient’s memories and subjective interpretations of what they are experiencing, studying depression with any accuracy is next to impossible. It’s not easy to report how you were feeling over the last 24 hours, much less the last week, and for most current depression measures that’s exactly what patients are asked to do.

We can’t rely on current research methods
In addition to relying on patient self-reporting, there are many other factors that confuse and muddle mental health research results.

For one thing, when dealing with human studies, there are so many symptoms associated with depression that two people in the same test group could have zero symptoms in common. Chances are that the same drugs won’t work for both of them, which affects the entire research effort.  Put another way, for conditions such as depression which are identified by a group of symptoms rather than a known primary cause, it is often the case that there are many different causes of the symptoms that make up the diagnosis of depression. Persistent pain provides an analogy: the many potential causes can be difficult to treat, or even unknown, with large numbers of us taking medications to reduce the symptom without addressing the cause.  The same occurs in depression.

Then there’s the fact that scientists often translate results from animal studies to humans, despite the fact that our brains differ in many key ways. Often, drugs that succeed in animal trials have no effect on human beings.

Money alone won’t solve the problem
Many people believe that throwing more money at depression research will advance the cause more quickly, but that’s simply not the case. The National Institute of Health (NIH) has already spent billions of dollars funding different organizations that study the brain. Investigators and institutions have vigorously argued for testing compounds that have different actions than marketed drugs and moving forward with studies, yet this research has yielded little interpretable or useful information because we haven’t had the baseline knowledge needed.

In the past, our discovery of psychiatric drugs has been mostly accidental. A doctor might prescribe a seizure medication, notice positive changes in a patient’s mood, and voilà, a new antidepressant was born. Because the drugs were already being tested on or used by humans, it was easy — and relatively inexpensive — for scientists to get the drugs tested and approved for mental health applications.

But as we’ve attempted to start from scratch with psychiatric medications, we’ve spent billions of dollars with disappointingly little to show for it.

When it comes to new drugs, the issue was (and is) finding and testing targets. A target is a biological process or area that a drug is created to address. Drug developers have become more and more skilled at finding compounds that engage such targets. But, while scientists have found at least 50 targets that they believe have the potential to improve the treatment of depression, none have been proven to be the case. And the cost of researching just one such target can hit several hundred million dollars with absolutely no guarantee that it will prove effective. As a result, many pharmaceutical companies aren’t willing to invest as they did in the past given today’s high costs and low probability of success.

Biomarkers and better science
We need to advance our understanding of the brain — and depression — before we can effectively test new drugs. One area that will make a major difference is biomarkers, that is, physical measures that can objectively identify depression. These would help us more accurately diagnose patients and eliminate much of the subjectivity that causes problems with mental health research.

Biomarkers can come in a number of forms. A biomarker could be a means of measuring the number of receptors for a new drug target or how much energy one part of your brain uses when you do a particular task. We can use functional MRIs, EEGs, and other emerging technologies as means of measurement. Sleep studies are a good example of the effective use of a type of biomarker. Researchers don’t need to rely on people telling them how they slept; instead, they measure and define stages of sleep with an EEG.

The good news is we believe there’ll be a lot of progress with biomarkers over the next several years. Once we have more such objective measures of brain function, we can more effectively sub-divide people into groups that have similarly altered brain function rather than relying on their subjective reports of how they feel.  This will allow us to identify sub-groups among patients diagnosed with depression who show benefit from novel treatments. The way studies are done now, such benefits in a sub-group would not be detected and a drug that might be a breakthrough for twenty percent of a study group of people with depression would be put back on the shelf.

Onwards and upwards
Despite the challenges we’ve faced in mental health research over the past several decades, I believe there’s plenty of reason for optimism. In my next piece, I’ll discuss recent developments in the field, how scientists are moving towards a more effective future, and the different ways advocates and patients can help push this issue along.

Your Turn

  • What do you think is the best approach for finding new, effective treatments for depression and why?

William Z. Potter, M.D., Ph.D, is Co-Chair Emeritus, Neuroscience Steering Committee for the Biomarkers Consortium of the Foundation for the National Institutes of Health and Sr. Advisor to Director, National Institute of Mental Health. Bill Potter earned his B.A., M.S., M.D., and Ph.D. at Indiana University, after which he functioned in positions of increasing responsibility and seniority over the next twenty-five years at the National Institutes of Health with a research focus on translational neuroscience.  While at the NIH, Bill was widely published and appointed to many societies, committees, and boards; roles which enabled him to develop a wide reputation as an expert in psychopharmacological sciences and championing the development of novel treatments for CNS disorders.

Bill left the NIH in 1996 to accept a position as Executive Director for early clinical neuroscience at Lilly Research Labs, and in 2004 joined Merck Research Labs as VP of Clinical Neuroscience, then the newly created position of Translational Neuroscience in 2006, a position from which he retired in January of 2011. His experience at Lilly and MRL in identifying, expanding and developing methods of evaluating CNS effects of compounds in human brain cover state of the art approaches across multiple modalities. These include brain imaging and cerebrospinal fluid proteomics as well as development of more sensitive clinical measures.  Bill continues as an Emeritus co-chair of the Neuroscience Steering Committee of the FNIH and serves as a Senior Advisor to the Director of the NIMH where he champions the position that more disciplined hypothesis testing of targets in humans through public/private partnerships is the best near term approach to moving CNS drug development forward for important neurologic and psychiatric illnesses.

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