Although the past 50 to 60 years of antidepressant drug development focusing on monoamines has benefited many patients with depression, currently available treatments are still less than optimal, with inadequate, lacking or delayed response posing major challenges.1
In this CINP symposium at the AsCNP, experts presented recent developments, remaining gaps, and future directions for the identification of clinical predictors and multimodal biomarkers that may elucidate the neurobiological underpinnings of depression and pave the way for better treatment outcomes, and the discovery of new treatments.
From clinical predictors to biomarkers and precision medicine – not quite there, yet
Professor Siegfried Kasper, Medical University of Vienna, Austria opened the symposium noting that even though as many as one third of patients do not achieve remission with initial pharmacotherapy, with some degree of treatment resistant depression,1 we still lack the tools to identify at an early stage those patients, who need advanced approaches beyond first and second-line treatments.
We still lack the tools to identify at an early stage those patients who need advanced approaches beyond first and second-line treatments
Large-scale, longitudinal studies of treatment approaches and treatment outcomes in real-world clinical practice have established a number of clinical predictors for treatment resistance, including comorbid anxiety, suicidality, and melancholic features.2 However, although clinical risk factors are an important step towards a personalized approach to treatment, in order to be of clinical utility, these insights need to be complemented by biological and mechanistical approaches that can link treatment response to testable biomarkers. Despite the identification of biomarker candidates, such as hippocampal volume structure and network connectivity,3 and despite advances in genetic and -omics technologies, Professor Kasper noted, a genuine breakthrough in biomarker research is yet to be seen. He highlighted the integration of epidemiological and clinical data with machine learning, genetic and -omics approaches as necessary for progressing prediction models further towards application in routine clinical practice.
Treatment-resistance or treatment-inadequacy? Beyond the monoamine paradigm
Shifting the perspective from patients to treatments, Professor Kasper highlighted the limitations of conventional antidepressant treatment, noting the extensive use of augmentation strategies seen in clinical practice as an indication that the actions provided by monoaminergic monotherapy are insufficient for a large group of patients.4
Rather than considering the illness resistant to treatment, we should consider our treatments inadequate for targeting the illness
Elaborating on this point, Professor Pierre Blier, University of Ottawa, Canada, proposed that rather than considering the illness resistant to treatment, we should consider our treatments inadequate for targeting the illness. Calling for a broader approach to mechanisms by considering, for instance interactions between brain circuits and the involvement of glutamatergic pathways in addition to monoaminergic, Professor Blier highlighted the potential for combination strategies with complementary mechanisms on different monoamines, such as low-dose adjunctive therapies with dopaminergic properties, to provide more effective and faster therapeutic action, potentially improving long-term treatment outcomes by shortening the time during which patients are ill, functionally impaired and at risk of suicide.5,6
A multidisciplinary approach in research: A window into the black box connecting biology and behavior – and into the future?
By integrating a wide range of technologies across neurobiological modalities, researchers are able to test mechanistic concepts and biomarker candidates in clinical studies, and thus gain insight into the link between clinical factors and biological variables.
Dr Carlos A Zarate Jr, Chief at the National Institute of Mental Health (NIMH), concluded the symposium closing the loop back to the previous lecturers, presenting ongoing research, which aims at connecting clinical factors - such as treatment response or modulation of specific behavioral dimensions - with biological correlates at various system levels.7 By integrating a wide range of technologies across neurobiological modalities, Dr Zarate explained, researchers are able to test mechanistic concepts and biomarker candidates in clinical studies, for instance by the use of longitudinal study designs that contrast biomarkers before, during and after a clinical intervention. Dr Zarate highlighted that such multidisciplinary translational approaches have pointed to the important role of neuroplasticity and cellular resilience in mood disorders, with measures of homeostatic dysfunction as a promising marker of biological subtypes with differential response to treatment,8 thus highlighting a new road for drug discovery that goes beyond the monoamine paradigm.
Our correspondent’s highlights from the symposium are meant as a fair representation of the scientific content presented. The views and opinions expressed on this page do not necessarily reflect those of Lundbeck.
