Wu Tsai Neurosciences Institute Seminar Series Presents
Conor Liston, MD, PhD
Department of Psychiatry and
Brain and Mind Research Institute
Weill Cornell Medicine
Host: Rob Malenka
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. Genome-wide association studies have identified dozens of genetic risk variants, but it remains unclear precisely how these genes contribute to depression pathophysiology and whether they operate differently in men and women. I will present the results of two related projects aimed at understanding how dysfunction in prefrontal brain networks gives rise to specific depressive symptoms and behaviors, and how synaptic remodeling in these circuits contributes to transitions between mood states.
First, using functional magnetic resonance imaging (fMRI) in a large multisite sample, we have shown that patients with depression can be subdivided into four neurophysiological subtypes defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of biomarkers (statistical classifiers) for diagnosing depression subtypes with high sensitivity and specificity in multisite validation and out-of-sample replication datasets. These subtypes cannot be differentiated based solely on clinical features, but they are associated with differing clinical symptom profiles. They also predict differential improvements in anhedonia, anxiety, and other depressive symptoms in response to transcranial magnetic stimulation of the dorsomedial prefrontal cortex. By mapping our functional connectivity data to gene expression microarray data from the Allen Human Brain Atlas, we show that regional differences in gene expression predict which circuits and networks exhibit abnormal connectivity in depression. Distinct gene sets predicted functional connectivity abnormalities in the subgenual cingulate cortex and nucleus accumbens in women and in the dorsal prefrontal cortex in men. These gene sets were strongly enriched for depression-related genes; genes with reduced expression in the female brain early in life; and genes implicated in synapse function and immune signaling.
In a second set of experiments, we set out to investigate the neurobiological mechanisms driving the induction and remission of depressive episodes over time. Using two-photon microscopy and chronically implanted microprisms for repeated longitudinal imaging of prefrontal microcircuits in mice, we show that the induction of depression-like behavior in multiple chronic stress models is associated with clustered, branch-specific postsynaptic spine loss on prefrontal projection neurons. Antidepressant-dose ketamine selectively rescues this effect, but only partially, with substantial stress-related synapse loss persisting, despite the normalization of behavior. Using two photon calcium imaging and fiber photometry to record from prefrontal circuits, we show that antidepressant-induced synaptogenesis in prefrontal projection neurons restores coordinated activity in multicellular ensembles that predict motivated escape behavior. These ensembles encode learned social hierarchical relationships, and are critical for mediating stress-resilient social interaction behavior. These findings implicate prefrontal cortical synaptogenesis in rescuing specific neural substrates of depression-like behavior and sustaining the remission after antidepressant treatment.