Mayuresh S. Korgaonkar

Identification of a Common Neurobiological Substrate for Mental Illness

IMPORTANCE Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness. OBJECTIVE To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis. DATA SOURCES PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data. DATA EXTRACTION AND SYNTHESIS Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach. MAIN OUTCOMES AND MEASURES We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition. RESULTS Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning. CONCLUSIONS AND REVELANCE We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.

Widespread reductions in gray matter volume in depression

Abnormalities in functional limbic–anterior cingulate–prefrontal circuits associated with emotional reactivity, evaluation and regulation have been implicated in the pathophysiology of major depressive disorder (MDD). However, existing knowledge about structural alterations in depression is equivocal and based on cohorts of limited sample size. This study used voxel-based morphometry (VBM) and surface-based cortical thickness to investigate the structure of these circuits in a large and well-characterized patient cohort with MDD. Non-geriatric MDD outpatients (n = 102) and age- and gender-matched healthy control participants (n = 34) provided T1-weighted magnetic resonance imaging data during their baseline visit as part of the International Study to Predict Optimized Treatment for Depression. Whole-brain VBM volumetric and surface-based cortical thickness assessments were performed voxel-wise and compared (at p < 0.05 corrected for multiple comparisons) between the MDD and control groups. MDD participants had reduced gray matter volume in the anterior cingulate cortex, regions of the prefrontal circuits, including dorsolateral and dorsomedial prefrontal cortices, and lateral and medial orbitofrontal cortices, but not in limbic regions. Additional reductions were observed cortically in the posterior temporal and parieto-occipital cortices and, subcortically in the basal ganglia and cerebellum. Focal cortical thinning in the medial orbitofrontal cortex was also observed for the MDD group. These alterations in volume and cortical thickness were not associated with severity of depressive symptoms. The findings demonstrate that widespread gray matter structural abnormalities are present in a well-powered study of patients with depression. The patterns of gray matter loss correspond to the same brain functional network regions that were previously established to be abnormal in MDD, which may support an underlying structural abnormality for these circuits.

Obesity Is Associated With Reduced White Matter Integrity in Otherwise Healthy Adults

Existing work demonstrates that obesity is independently associated with cognitive dysfunction and macrostructural brain changes; however, little is known about the association between obesity and white matter (WM) integrity. We explore this relationship in a large cohort of otherwise healthy subjects. The present study classified 103 adult participants from the Brain Resource International Database between 21 and 86 years of age without history of neurological, medical, or psychiatric illness according to BMI (normal weight, overweight, obese) and subjected them to diffusion tensor imaging (DTI). Resulting fractional anisotropy (FA) indexes for the corpus callosum and fornix were examined in relation to BMI and age in a multiple regression framework. Results indicated that increasing BMI was independently associated with lower FA in the genu, splenium, and fornix, and a BMI × age interaction emerged for FA in the splenium and body of the corpus callosum. When categorized, obese persons demonstrated lower FA than normal and overweight persons for all WM indexes, but no FA differences emerged between overweight and normal persons. Results indicate both a direct association between obesity and reduced WM tract integrity and an interaction between obesity and aging processes on certain WM tracts in otherwise healthy adults. While such findings suggest a possible role for adiposity in WM dysfunction and associated cognitive deficits, prospective studies are needed to clarify the nature of these relationships and elucidate underlying mechanisms.

Loss of White Matter Integrity in Major Depressive Disorder: Evidence Using Tract-Based Spatial Statistical Analysis of Diffusion Tensor Imaging

White matter (WM) has been shown to be affected in elderly patients with major depressive disorders (MDD). There is only limited evidence of WM structural abnormalities in nongeriatric MDD patients. This study investigates WM microstructural integrity in nongeriatric MDD patients recruited as part of the International Study to Predict Optimized Treatment in Depression clinical trial and establishes the validity of diffusion tensor imaging measures for the investigation of depression. Baseline diffusion tensor imaging data from 29 nongeriatric MDD participants (11 with melancholia) and 39 healthy control participants were used in this analysis. We performed tract‐based spatial statistics analyses to evaluate WM microstructural integrity (1) between all healthy controls and all MDD participants, (2) between melancholic and nonmelancholic MDD participants, and (3) between each subgroup (melancholic and nonmelancholic) and controls. Significant WM integrity deficits were seen only for the melancholic MDD participants compared with controls. Compared with controls, melancholic participants showed an average reduction of 7.8% in fractional anisotropy over WM regions associated with the limbic system, dorsolateral prefrontal cortex, thalamic projection fibers, corpus callosum, and other association fibers. These fractional anisotropy deficits were also associated with decreased axial and increased radial diffusivity in these WM regions, suggesting a pattern of decreased myelination or other degeneration change. Our findings of WM structural abnormalities associated with the limbic system, the frontal cortex, and the thalamus support the prevailing theory of limbic‐dorsolateral prefrontal cortex‐thalamic dysfunction in depression. Our results also suggest that these deficits are most prominent in the melancholic subtype of MDD. Hum Brain Mapp, 2011.

Abnormal Structural Networks Characterize Major Depressive Disorder: A Connectome Analysis

BACKGROUND Major depressive disorder (MDD) has been shown to be associated with a disrupted topological organization of functional brain networks. However, little is known regarding whether these changes have a structural basis. Diffusion tensor imaging (DTI) enables comprehensive whole-brain mapping of the white matter tracts that link regions distributed throughout the entire brain, the so-called human connectome. METHODS We examined whole-brain structural networks in a cohort of 95 MDD outpatients and 102 matched control subjects. Structural networks were represented by an 84 × 84 connectivity matrix representing probabilistic white matter connections between 84 parcellated cortical and subcortical regions using DTI tractography. Network-based statistics were used to assess differences in the interregional connectivity matrix between the two groups, and graph theory was used to examine overall topological organization. RESULTS Our network-based statistics analysis demonstrates lowered structural connectivity within two distinct brain networks that are present in depression: the first primarily involves the regions of the default mode network and the second comprises the frontal cortex, thalamus, and caudate regions that are central in emotional and cognitive processing. These two altered networks were observed in the context of an overall preservation of topology as reflected as no significant group differences for the graph-theory measures. CONCLUSIONS This is the first report to use DTI to show the structural connectomic alterations present in MDD. Our findings highlight that altered structural connectivity between nodes of the default mode network and the frontal-thalamo-caudate regions are core neurobiological features associated with MDD.

Limbic dysregulation is associated with lowered heart rate variability and increased trait anxiety in healthy adults

We tested whether dynamic interaction between limbic regions supports a control systems model of excitatory and inhibitory components of a negative feedback loop, and whether dysregulation of those dynamics might correlate with trait differences in anxiety and their cardiac characteristics among healthy adults.

Testing the white matter retrogenesis hypothesis of cognitive aging

The retrogenesis hypothesis postulates that late-myelinated white matter fibers are most vulnerable to age- and disease-related degeneration, which in turn mediate cognitive decline. While recent evidence supports this hypothesis in the context of Alzheimers disease, it has not been tested systematically in normal cognitive aging. In the current study, we examined the retrogenesis hypothesis in a group (n = 282) of cognitively normal individuals, ranging in age from 7 to 87 years, from the Brain Resource International Database. Participants were evaluated with a comprehensive neuropsychological battery and were imaged with diffusion tensor imaging. Fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (DA), measures of white matter coherence, were computed in 2 prototypical early-myelinated fiber tracts (posterior limb of the internal capsule, cerebral peduncles) and 2 prototypical late-myelinated fiber tracts (superior longitudinal fasciculus, inferior longitudinal fasciculus) chosen to parallel previous studies; mean summary values were also computed for other early- and late-myelinated fiber tracts. We examined age-associated differences in FA, RD, and DA in the developmental trajectory (ages 7-30 years) and degenerative trajectory (ages 31-87 years), and tested whether the measures of white matter coherence mediated age-related cognitive decline in the older group. FA and DA values were greater for early-myelinated fibers than for late-myelinated fibers, and RD values were lower for early-myelinated than late-myelinated fibers. There were age-associated differences in FA, RD, and DA across early- and late-myelinated fiber tracts in the younger group, but the magnitude of differences did not vary as a function of early or late myelinating status. FA and RD in most fiber tracts showed reliable age-associated differences in the older age group, but the magnitudes were greatest for the late-myelinated tract summary measure, inferior longitudinal fasciculus (late fiber tract), and cerebral peduncles (early fiber tract). Finally, FA in the inferior longitudinal fasciculus and cerebral peduncles and RD in the cerebral peduncles mediated age-associated differences in an executive functioning factor. Taken together, the findings highlight the importance of white matter coherence in cognitive aging and provide some, but not complete, support for the white matter retrogenesis hypothesis in normal cognitive aging.

Hippocampal volume varies with educational attainment across the life-span

Socioeconomic disparities—and particularly differences in educational attainment—are associated with remarkable differences in cognition and behavior across the life-span. Decreased educational attainment has been linked to increased exposure to life stressors, which in turn have been associated with structural differences in the hippocampus and the amygdala. However, the degree to which educational attainment is directly associated with anatomical differences in these structures remains unclear. Recent studies in children have found socioeconomic differences in regional brain volume in the hippocampus and amygdala across childhood and adolescence. Here we expand on this work, by investigating whether disparities in hippocampal and amygdala volume persist across the life-span. In a sample of 275 individuals from the BRAINnet Foundation database ranging in age from 17 to 87, we found that socioeconomic status (SES), as operationalized by years of educational attainment, moderates the effect of age on hippocampal volume. Specifically, hippocampal volume tended to markedly decrease with age among less educated individuals, whereas age-related reductions in hippocampal volume were less pronounced among more highly educated individuals. No such effects were found for amygdala volume. Possible mechanisms by which education may buffer age-related effects on hippocampal volume are discussed.

Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial.

Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test–retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin–norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen’s d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward ‘normalization’ post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen’s d effect size 1.5; classification accuracy, 81%). Non-responders to venlafaxine-XR showed pre-treatment hyper-reactivity, which progressed to hypo-reactivity rather than normalization post-treatment, and hypo-reactivity post-treatment was abnormal compared to controls. Impaired amygdala activation has not previously been highlighted in the general vs differential prediction of antidepressant outcomes. Amygdala hypo-reactivity to emotions signaling reward and threat predicts the general capacity to respond to antidepressants. Amygdala hyper-reactivity to sad emotion is involved in a specific non-response to a serotonin–norepinephrine reuptake inhibitor. The findings suggest amygdala probes may help inform the personal selection of antidepressant treatments.

Using standardized fMRI protocols to identify patterns of prefrontal circuit dysregulation that are common and specific to cognitive and emotional tasks in major depressive disorder: first wave results from the iSPOT-D study.

Functional neuroimaging studies have implicated dysregulation of prefrontal circuits in major depressive disorder (MDD), and these circuits are a viable target for predicting treatment outcomes. However, because of the heterogeneity of tasks and samples used in studies to date, it is unclear whether the central dysfunction is one of prefrontal hyperreactivity or hyporeactivity. We used a standardized battery of tasks and protocols for functional magnetic resonance imaging, to identify the common vs the specific prefrontal circuits engaged by these tasks in the same 30 outpatients with MDD compared with 30 matched, healthy control participants, recruited as part of the International Study to Predict Optimized Treatment in Depression (iSPOT-D). Reflecting cognitive neuroscience theory and established evidence, the battery included cognitive tasks designed to assess functions of selective attention, sustained attention-working memory and response inhibition, and emotion tasks to assess explicit conscious and implicit nonconscious viewing of facial emotion. MDD participants were distinguished by a distinctive biosignature of: hypoactivation of the dorsolateral prefrontal cortex during working memory updating and during conscious negative emotion processing; hyperactivation of the dorsomedial prefrontal cortex during working memory and response inhibition cognitive tasks and hypoactivation of the dorsomedial prefrontal during conscious processing of positive emotion. These results show that the use of standardized tasks in the same participants provides a way to tease out prefrontal circuitry dysfunction related to cognitive and emotional functions, and not to methodological or sample variations. These findings provide the frame of reference for identifying prefrontal biomarker predictors of treatment outcomes in MDD.