Develop an integrated model of anhedonic depression capturing both internal biological factors and externally-manifested and quantifiable symptom-correlated biometrics and behavioral measures. This model should stratify people into those who will be treatment sensitive and those who will be treatment resistant with 80% accuracy, consistent with the current 20% false negative rate for mammograms. The model should also be sufficient to match responsive patients to their appropriate treatment regimen rapidly, including novel or existing behavior modification, psychotherapy, medication, and neurostimulation options.
Depression is a complex biological illness. We need treatments to match.
The latest worldwide survey of global health underscores the devastating impact of depression. Depression was ranked as the 3rd highest cause of disability across all illnesses, resulting in approximately 43 million years lost to disability (YLD). In only a single year, 264 million people suffer from depression, and 800,000 lives are lost to suicide. Narrowing in on the United States, almost 7% of adults experience an episode of depression each year, costing an estimated $210.5 billion due to the combination of treatment costs and productivity loss. Consistent with this enormous disease burden, the NIH has spent over $22 billion on depression research over the last 20 years – more than for any other mental illness, including addiction, schizophrenia, or autism. But despite this massive investment, only 1 in 3 patients substantially responds to currently available medication or psychotherapy treatments.
Why are we stuck? The modern practices of psychiatry and psychology are grounded in neuroscience and biology. We understand that synaptic connections serve as the currency of neural communication, and that strengthening or weakening these connections can facilitate learning new behavioral strategies and ways of looking at the world. Through studies in both animal models and humans, we have discovered that emotional states are encoded in complex neural network activity patterns, and that directly changing these patterns via brain stimulation can shift mood. We also know that disruption of these delicately balanced networks can lead to neuropsychiatric illness.
Based on this understanding that psychiatric symptoms are rooted in biology, all existing drug therapies for depression target biological mechanisms. Selective serotonin reuptake inhibitors (SSRIs) bind to the serotonin transporter, leading to increased serotonin concentration in the synaptic cleft and a cascade of downstream functional and structural consequences. Although the exact mechanism of action of the fast-acting antidepressant ketamine is still being investigated, it is known to be an NMDA-receptor antagonist. Brexanolone, which is the newest FDA-approved antidepressant for the indication of post-partum depression, is a neuroactive steroid that is a positive allosteric modulator of the GABA receptor. We have now even solved the crystal structures of psychiatric drugs binding to their targeted receptors. Since at least the 1960’s, with the first indications that alterations in levels of catecholamines such as dopamine can lead to depressed mood, we have known that depression is biologically based, and that treatments need to address these underlying biological problems.
Yet, these biologically based treatments are not being matched to the biology of the human beings they’re being used in. According to standard treatment guidelines currently recommended by the American Psychiatric Association, the first-line pharmacotherapeutic treatment for depression is a randomly selected SSRI. And if that doesn’t work, the next step is switching to another randomly selected SSRI, followed by augmentation with an additional agent or switching to an alternative medication class. It is a brute force process guided almost exclusively by qualitative data and subjective self-report. And the impact of each new medication change can take between 2-6 months to assess. This current state of affairs leads to time lost for both patients and their loved ones, unnecessary side effects, discouragement, and – perhaps most importantly – continued progression towards end-stage illness.
What needs to change? To make meaningful change, we need to match treatments to the specific biology of the people receiving them.
We envision a world in which diagnosing anhedonic depression is as straightforward as getting a mammogram, and stratification into a treatment plan has the same speed as current algorithms after breast biopsy. This necessitates a general shift of mindset in an important way. Depression can be a terminal illness, just like breast cancer. Rapid, targeted intervention is therefore vital to prevent progression. Initially selecting the treatment with the highest likelihood of working for an individual patient based on their specific biology is therefore of high value, because in addition to decreasing the total time of suffering, key goals include avoiding unnecessary side effects and limiting treatment-associated risks. To that end, our goals are to achieve:
1. Rapid patient stratification and treatment matching: Develop an integrated model of anhedonic depression capturing both internal biological factors and externally-manifested and quantifiable symptom-correlated biometrics and behavioral measures. This model should stratify people into those who will be treatment sensitive and those who will be treatment resistant with 80% accuracy, consistent with the current 20% false negative rate for mammograms. The model should also be sufficient to match responsive patients to their appropriate treatment regimen rapidly, including novel or existing behavior modification, psychotherapy, medication, and neurostimulation options. Currently 33% of depressed people have significant symptom reduction with the initial treatment selected, while an additional 21-33% of people require between 2-4 treatment trials to achieve remission. Our goal is to double the number of people who receive an effective treatment on the first try.
1a. The model should capture multiple levels of investigation (e.g. genome, phenome, network connectivity, metabolome, microbiome, reward processing, plasticity levels, HPA axis function).
1b. The model should seek to leverage high frequency patient-worn or in-home measurements in addition to those obtained in the clinic, hospital, or laboratory.
1c. The integrated model should predict the relationship between genome, metabolome (particularly, but not exclusively, from CSF), microbiome, and resting-state connectivity to anhedonia symptoms, reward processing, and treatment response in depressed individuals.
1d. Predictive validity should be verified in new cohorts either held out from existing samples or collected during the study period.
2. Identification of mechanisms underlying treatment-resistant anhedonic depression: Define the biological basis of anhedonic depression with the goal of identifying effective treatments for half of non-responsive patients, as measured by a decrease of ≥50% on current gold-standard suicidality, depression, and anhedonia scales (HAM-D, BDI, SHAPS). We are particularly interested in developing patient-personalized data-driven “Intensive Care” treatment regimens – inclusive of both new and existing lifestyle, drug, psychotherapy, and device interventions – that reduce suicide risk in the top quintile of patient severity. High density behavioral measures should be used in this high-risk population to intensively track symptoms and environmental factors (exercise, sleep, social interactions, etc.) in those who are the most likely to progress to terminal illness, with a goal of developing patient-controlled “alarms” to trigger suggestions to seek help or more intensive interventions. Our intent is to have the same impact on the survivability of severe, treatment-resistant depression that advances in diagnostics and treatment have had on the survivability of breast cancer. Namely, we want 85% of people to survive their suicidal anhedonic depression for at least 5 years– and perhaps a full lifetime– after diagnosis.
Please see the Master Research Funding Agreement page for more information and learn how to become a member.