Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality

Abstract

Suicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We performed neuroimaging-guided RNA-sequencing in two studies to test the hypothesis that imaging-localized gray matter volume (GMV) loss in mood disorders, harbors gene-expression changes associated with disease morbidity and related suicide mortality in an independent postmortem cohort. To do so, first, we conducted study 1 using an anatomical likelihood estimation (ALE) MRI meta-analysis including a total of 47 voxel-based morphometry (VBM) publications (i.e. 26 control versus (vs) major depressive disorder (MDD) studies, and 21 control vs bipolar disorder (BD) studies) in 2387 (living) participants. Study 1 meta-analysis identified a selective anterior insula cortex (AIC) GMV loss in mood disorders. We then used this results to guide study 2 postmortem tissue dissection and RNA-Sequencing of 100 independent donor brain samples with a life-time history of MDD (N = 30), BD (N = 37) and control (N = 33). In study 2, exploratory factor-analysis identified a higher-order factor representing number of Axis-1 diagnoses (e.g. substance use disorders/psychosis/anxiety, etc.), referred to here as morbidity and suicide-completion referred to as mortality. Comparisons of case-vs-control, and factor-analysis defined higher-order-factor contrast variables revealed that the imaging-identified AIC GMV loss sub-region harbors differential gene-expression changes in high morbidity-&-mortality versus low morbidity-&-mortality cohorts in immune, inflammasome, and neurodevelopmental pathways. Weighted gene co-expression network analysis further identified co-activated gene modules for psychiatric morbidity and mortality outcomes. These results provide evidence that AIC anatomical signature for mood disorders are possible correlates for gene-expression abnormalities in mood morbidity and suicide mortality.

Introduction

Major depressive disorder and bipolar disorder ⎯ here together referred to as mood disorders, are the third leading cause of the global disease burden (Collins et al., 2011; Murray et al., 2012). Mood disorders account for the majority of completed suicides (Waern et al., 2002; Marangell et al., 2006) and they were linked to ~48,000 suicides in the United States in 2018 alone (American Foundation for Suicide Prevention, 2019). However, the convergent neurobiological basis for mood symptoms/syndromes and suicide is unknown, limiting advances in developing novel interventions.

Neuroimaging studies have identified reduction in gray matter volume (GMV) in the anterior insular cortex (AIC) and anterior cingulate cortex (ACC) in association with diagnosis of psychiatric disorders in general (Goodkind et al., 2015), and the regional GMV volume reductions in these AIC and ACC network have been especially implicated in mood disorder diagnoses in particular (Goodkind et al., 2015; Wise et al., 2017). Neurobiological integrity of the right AIC is shown to (a) predict mood diagnostic severity (Hatton et al., 2012), (b) modulate subjective responses to distress, pain, and psychosocial adversity (Wager et al., 2013; Eisenberger, 2015), (c) regulate affective interoception (Craig, 2009; Khalsa et al., 2018), (d) associate with stress-related inflammatory markers (Slavich et al., 2010), and (e) predict psycho- and pharmaco-therapeutic efficacy in mood disorders (McGrath et al., 2013). AIC-ACC functional connectivity during affective processing differentiated mood disorder suicide-attempters from non-attempters (Pan et al., 2013). Furthermore, abnormalities in AIC volume and synaptic abnormalities are linked to suicidal-behavior in mood disorder (Wagner et al., 2012; Mathews et al., 2013). AIC response to stress is shown to impact hypothalamic-pituitary-adrenal (HPA) axis-driven inflammatory responses (Khalsa et al., 2013), which may serve to exacerbate mood disorder associated psychiatric morbidity and suicidal-behavior (Oquendo et al., 2014; Wohleb et al., 2016). Although a preponderance of evidence supports abnormal AIC integrity in psychosocial distress (Shneidman, 1998; Mee et al., 2011; Wager et al., 2013) and mood/comorbid psychiatric symptoms, an underlying functional genetic contribution in terms of functional gene-expression changes for these abnormalities remains largely unknown.

The lack of a well-defined relationship between aberrant brain structure and function with underlying molecular changes within these abnormal brain regions is an impediment to understanding pathophysiology. Moreover, evidence for shared genetic mechanisms underlying psychiatric diagnoses (Brainstorm consortium, Anttila et al., 2018) is not well-integrated with brain imaging correlates of psychiatric disease-morbidity and specific behaviors, in this case, suicide. In the present study, MRI meta-analysis was used to test the hypothesis that reduced AIC volume will be the most prominent neuroanatomical signature for mood disorder diagnoses. We confirmed this hypothesis with our meta-analytic findings in study 1 and then used this anatomical hallmark to guide dissection of postmortem brain tissue for analyses of molecular/gene-expression signatures that could pave the way for precision profiling of gene functions underlying mood symptoms across diagnoses in clinically-relevant brain sub-regions in study 2. This approach enabled us to further test the hypothesis that the voxel-based morphometry (VBM) imaging meta-analysis defined in study 1 will harbor postmortem gene-expression signatures for psychiatric disease morbidity and related suicide-mortality in postmortem mood disorder brains, thereby providing a neurobiological framework for characterizing convergent neural-and-gene expression signatures for behavioral brain diseases.