Resting-state connectivity biomarkers define neuro-physiological subtypes of depression
Channel: Ludmer Centre
Date: 2019-03-25

Dr Conor Liston's research focuses on the interface between systems neuroscience and biological psychiatry in order to define the circuit mechanisms by which neurons in the prefrontal cortex contribute to cognitive and emotional processes and how they are disrupted in neuropsychiatric disease states. Liston Lab, Weill Cornell Medicine Feil Family Brain & Mind Research Institute, NY, US

Abstract: Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample (n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes (‘biotypes’) defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82–93%) sensitivity and specificity for depression subtypes in multisite validation (n = 711) and out-of-sample replication (n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy (n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.

Lecture date: Nov. 27, 2018 
Lecture series @ McGill University, partners:
- Ludmer Centre for Neuroinformatics & Mental Health 
- Quantitative Life Sciences PhD program 
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