Toward precision medicine for depression: admitting ignorance and focusing on failures
Authors: A. John Rush
Journal: World Psychiatry (2016)

I first recognized what R. Perlis1 calls “artisanal practice” as a medical student in Liberia. Witch doctors – basically the local primary and psychiatric care providers at the time – regularly engaged in “throwing the bones”. Chicken bones, often in a bag but sometimes in hand, were shaken and thrown on the ground, resulting in a unique pattern which served as the basis for recommendation(s) offered to each “patient”. “Throwing the bones” was common and well accepted. So much so that it was rare to have dehydrated neonates arrive at the hospital without dung spread over their depressed fontanelles, courtesy of the “doctor”. Personalized care – maybe; precision medicine – not so much. But let me also defend some important aspects of personalized care. Organizing treatment steps based on reasonable Hippocratic principles and logic is appropriate2. Avoiding medications that lower seizure thresholds in patients at risk, especially when safer options exist, is smart. My guess is that maybe 7-15% of depressed patients should avoid certain medications for medical reasons. In sum, let's recognize that we too are throwing the bones when selecting among antidepressant medications for specific patients, while we avoid certain treatments in selected patients for safety reasons. To advance the precision of treatment selection, I agree with Perlis that we must provide systematic patient education, become adroit in the implementation of measurement-based care (to enhance efficacy and tolerability, and to reduce variations that interfere with signal detection) and shed our information about how to choose among treatments. Let's leave the bones in the bag! We desperately need more knowledge about how to accomplish our clinical tasks, including treatment selection. However, we seem to get entrenched in our beliefs and routines, and our own administrative, reimbursement and legal cultures. I'll bet that the Liberian “doctors” are still able change practices more easily than we can! Perlis highlights the issue of slow adoption with his experience in pharmacogenetic testing research. Clinicians are moved almost entirely by what impacts their patients’ outcomes, despite evidence of cost-effectiveness. There is still a paucity of research capable of changing the minds of clinicians and patients. Uptake and changes in practice would speed up if we had more research that focused on questions pivotal to clinician-patient decisions that result in clear evidence of benefit to substantial numbers of patients3. Issues in implementation would be clarified and uptake facilitated by addressing specific questions, such as: when in the course of treatment steps and with which medications is pharmacogenetic testing useful? Or, can we identify which patients have treatment-resistant depression at the outset?4 Let's assume that we have engineered consistent high-quality, measurement-based care, and have electronic health records and a cadre of educated and collaborative patients. Having somehow set this table to aggressively pursue precision medicine, the question becomes: do any of our prior successes in matching treatments and patients suggest a preferred path forward? One major focus might be on identifying with a high degree of certainty which patients are very likely to not respond or succeed (i.e., to go after treatment failures). Depression is not unchecked cancer, with its generally predictable downhill and often terminal course. Success is an exception in cancer without treatment. Therefore, in cancer treatment research, a focus on success makes sense. Even after a successful cancer treatment begins to fail, we can learn from these failures. Depression, on the other hand, is a heterogeneous syndrome that has a highly variable course which is affected by changes in support, stresses, comorbidities and substances to name but a few. Adding to these challenges is the fact that only a small proportion of the “successes” will be specifically responding to the medication. By focusing on depressed persons whose treatments have failed, we can learn which features of our patients or their treatments are contributing to the failures. An example of this in another area of study would be the pool of anemic patients who have been non-responsive to iron. This group would be enriched in patients with B12 deficiency. This B12 deficient subset might be easier to detect, especially in large patient samples and with the use of machine learning. As a further illustration of the potential value of a focus on failures, consider how atypical depression grew out of a recognition that some depressed patients, often with atypical features, fared poorly with tricyclic antidepressants but succeeded with monoamine oxidase inhibitors5. Perlis’ own work to define risk factors for treatment-resistant depression4 also illustrates how a failure focus can be productive. His results indicated that there is a meaningful proportion of treatment-resistant patients (maybe 25%) who can be specifically identified by the measures used. Uher et al6 also hit pay dirt with a failure focus, finding that anhedonic depressed patients do poorly with serotonin/noradrenaline reuptake blockers. Hedonically-impaired patients with treatment-resistant depression may have a dysfunctional mesolimbic dopamine system. Fawcett et al7 recently found higher doses of adjunctive pramipexole to be associated with substantial and largely sustained benefits to treatment-resistant depression patients with severely impaired interest/activity. Finally, to advance precision medicine, do we really need to wait to change psychiatric practices broadly? Culture changes are led by the few; almost never by the many. Multi-site registries that engage only those providers who are willing to make the changes above could generate large numbers of subjects for computations that involve large numbers of variables. I suspect that even randomization after the first step (though not essential) would be feasible in such registries and might well speed up discovery, given providers that possess the requisite curiosity and humility. In conclusion, I largely concur with the challenges raised by R. Perlis in moving into the precision medicine space. These problems are all solvable as they are all man-made. Certainly better patient education, widespread use of measurement-based care and a willingness to throw away those bones are essential next steps for a coalition of the willing. A focus on failures may be a fertile field to till. A. John Rush Duke-National University of Singapore, Singapore