Atypical brain aging and its association with working memory performance in major depressive disorder.

BACKGROUND: Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to aging. Yet, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool quantifying normative neurodevelopmental trajectories. METHODS: 304 MDD participants and 236 non-depressed controls were recruited and scanned from three studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for: a) differences in MDD relative to controls; b) differences in individuals with versus without severe childhood maltreatment; and c) correlations with depressive symptom severity, neurocognitive assessment domains, or escitalopram treatment response. RESULTS: Brain centiles were significantly lower in the MDD group compared to controls. It was also significantly correlated with working memory in controls, but not the MDD group. No significant associations were observed in depression severity or antidepressant treatment response with brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. CONCLUSIONS: Consistent with prior work on machine learning models that predict "brain age", brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications on neurocognitive deficits associated with aging-related cognitive function.

Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample.

BACKGROUND: Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample. METHODS: We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes. RESULTS: The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. CONCLUSIONS: Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

An empirical analysis of structural neuroimaging profiles in a staging model of depression.

We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study.

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term ß = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

Cardiovascular biomarkers of response to accelerated low frequency repetitive transcranial magnetic stimulation in major depression.

BACKGROUND AND OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) is an effective and safe treatment for major depressive disorder (MDD). rTMS is in need of a reliable biomarker of treatment response. High frequency (HF) dorsolateral prefrontal cortex (DLPFC) rTMS has been reported to induce significant changes in the cardiac activity of MDD patients. Low frequency DLPFC rTMS has many advantages over HF-DLPFC rTMS and thus this study aims to further investigate the effect of low frequency 1 Hz right hemisphere (R)-DLPFC rTMS on the cardiac activity of MDD patients, as well as the potential of using electrocardiogram (ECG) parameters as biomarkers of treatment outcome. METHODS: Baseline ECG sessions were performed for 19 MDD patients. All patients then underwent 40 sessions of accelerated 1 Hz R-DLPFC rTMS one week after the baseline session. RESULTS: Heart rate (HR) significantly decreased from the resting period to the first and third minute of the 1 Hz R-DLPFC rTMS period. Resting HR was found to have a significant negative association with treatment outcome. Prior to Bonferroni correction, HR during stimulation and the degree of rTMS-induced HR reduction were significantly negatively associated with treatment outcome. No significant changes were observed for the heart rate variability (HRV) parameters. LIMITATIONS: Sample size (n = 19); the use of electroencephalography equipment for ECG; lack of respiration monitoring; relatively short recording duration for HRV parameters. CONCLUSION: This novel study provides further preliminary evidence that ECG may be utilized as a biomarker of rTMS treatment response in MDD. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04376697.

Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression.

The neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8, a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation.

Neuroimaging Correlates of Treatment Response with Psychedelics in Major Depressive Disorder: A Systematic Review.

Preliminary evidence supports the use of psychedelics for major depressive disorder (MDD). However, less attention has been given to the neural mechanisms behind their effects. We conducted a systematic review examining the neuroimaging correlates of antidepressant response following psychedelic interventions for MDD. Through MEDLINE, Embase, and APA PsycINFO, 187 records were identified and 42 articles were screened. Six published studies and one conference abstract were included. Five ongoing trials were included from subjective outcomesTrials.gov. Our search covered several psychedelics, though included studies were specific to psilocybin, ayahuasca, and lysergic acid diethylamide. Three psilocybin studies noted amygdala activity and functional connectivity (FC) alterations that correlated with treatment response. Two psilocybin studies reported that FC changes in the medial and ventromedial prefrontal cortices correlated with treatment response. Two trials from a single study reported global decreases in brain network modularity which correlated with antidepressant response. One ayahuasca study reported increased activity in the limbic regions following treatment. Preliminary evidence suggests that the default mode and limbic networks may be a target for future research on the neural mechanisms of psychedelics. More data is required to corroborate these initial findings as the evidence summarized in this review is based on four datasets.

Comparison of Functional and Structural Neural Network Features in Older Adults With Depression With vs Without Apathy and Association With Response to Escitalopram: Secondary Analysis of a Nonrandomized Clinical Trial.

Importance: Apathy is prevalent among individuals with late-life depression and is associated with poor response to pharmacotherapy, including chronicity and disability. Elucidating brain networks associated with apathy and poor treatment outcomes can inform intervention development. Objectives: To assess the brain network features of apathy among individuals with late-life depression and identify brain network abnormalities associated with poor antidepressant response. Design, Setting, and Participants: This secondary analysis of a single-group, open-label nonrandomized clinical trial of escitalopram conducted at an outpatient geriatric psychiatry clinic enrolled 40 adults aged 59 to 85 years with major depressive disorder from July 1, 2012, to July 31, 2019. Interventions: After a 2-week washout period, participants received escitalopram titrated to a target of 20 mg/d for 12 weeks. Main Outcomes and Measures: Baseline and posttreatment magnetic resonance imaging (MRI), clinical, and cognitive assessments were conducted. Functional MRI was used to map group differences in resting state functional connectivity (rsFC) of the salience network, and diffusion MRI connectometry was performed to evaluate pathway-level disruptions in structural connectivity. The Apathy Evaluation Scale was used to quantify apathy, and the Hamilton Depression Rating Scale (HAM-D) was used to quantify the primary outcome of depression severity. Results: Forty participants (26 women [65%]; mean [SD] age, 70.0 [6.6] years [range, 59-85 years]) with depression were included; 20 participants (50%) also had apathy. Relative to nonapathetic participants with depression, those with depression and apathy had lower rsFC of salience network seeds with the dorsolateral prefrontal cortex (DLPFC), premotor cortex, midcingulate cortex, and paracentral lobule and greater rsFC with the lateral temporal cortex and temporal pole (z score >2.7; Bonferroni-corrected threshold of P < .0125). Compared with participants without apathy, those with apathy had lower structural connectivity in the splenium, cingulum, and fronto-occipital fasciculus (t score >2.5; false discovery rate-corrected P = .02). Twenty-seven participants completed escitalopram treatment; 16 (59%) achieved remission (HAM-D score <10). Lower insula-DLPFC/midcingulate cortex rsFC was associated with less symptomatic improvement (HAM-D % change) (ß [df] = 0.588 [26]; P = .001) and a higher likelihood of nonremission (odds ratio, 1.041 [95% CI, 1.003-1.081]; P = .04) after treatment and, in regression models, was a mediator of the association between baseline apathy and persistence of depression. Lower dorsal anterior cingulate-DLPFC/paracentral rsFC was associated with residual cognitive difficulties on measures of attention (ß [df] = 0.445 [26]; P = .04) and executive function (ß [df] = 0.384 [26]; P = .04). Conclusions and Relevance: This study suggests that disturbances in connectivity between the salience network and other large-scale networks that support goal-directed behavior may give rise to apathy and may be associated with poor response of late-life depression to antidepressant pharmacotherapy. These network disturbances may serve as targets for novel interventions. Trial Registration: ClinicalTrials.gov Identifier: NCT01728194.

Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review.

Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.

Estimated Regional White Matter Hyperintensity Burden, Resting State Functional Connectivity, and Cognitive Functions in Older Adults.

OBJECTIVE: White matter hyperintensities (WMH) are linked to deficits in cognitive functioning, including cognitive control and memory; however, the structural, and functional mechanisms are largely unknown. We investigated the relationship between estimated regional disruptions to white matter fiber tracts from WMH, resting state functional connectivity (RSFC), and cognitive functions in older adults. DESIGN: Cross-sectional study. SETTING: Community. PARTICIPANTS: Fifty-eight cognitively-healthy older adults. MEASUREMENTS: Tasks of cognitive control and memory, structural MRI, and resting state fMRI. We estimated the disruption to white matter fiber tracts from WMH and its impact on gray matter regions in the cortical and subcortical frontoparietal network, default mode network, and ventral attention network by overlaying each subject's WMH mask on a normative tractogram dataset. We calculated RSFC between nodes in those same networks. We evaluated the interaction of regional WMH burden and RSFC in predicting cognitive control and memory. RESULTS: The interaction of estimated regional WMH burden and RSFC in cortico-striatal regions of the default mode network and frontoparietal network was associated with delayed recall. Models predicting working memory, cognitive inhibition, and set-shifting were not significant. CONCLUSION: Findings highlight the role of network-level structural and functional alterations in resting state networks that are related to WMH and impact memory in older adults.

A pilot trial of repetitive transcranial magnetic stimulation of the dorsomedial prefrontal cortex in anorexia nervosa: resting fMRI correlates of response.

BACKGROUND: Patients with anorexia nervosa (AN) face severe and chronic illness with high mortality rates, despite our best currently available conventional treatments. Repetitive transcranial magnetic stimulation (rTMS) has shown increasing efficacy in treatment-refractory cases across a variety of psychiatric disorders comorbid with AN, including major depression, Obsessive Compulsive Disorder (OCD), and Post traumatic Stress Disorder (PTSD). However, to date few studies have examined the effects of a course of rTMS on AN pathology itself. METHODS: Nineteen patients with AN underwent a 20-30 session open-label course of dorsomedial prefrontal rTMS for comorbid Major Depressive Disorder (MDD) ± PTSD. Resting-state functional MRI was acquired at baseline in 16/19 patients. RESULTS: Following treatment, significant improvements were seen in core AN pathology on the EDE global scale, and to a lesser extent on the shape and weight concerns subscales. Significant improvements in comorbid anxiety, and to a lesser extent depression, also ensued. The greatest improvements were seen in patients with lower baseline functional connectivity from the dorsomedial prefrontal cortex (DMPFC) target to regions in the right frontal pole and left angular gyrus. CONCLUSIONS: Despite the limited size of this preliminary, open-label study, the results suggest that rTMS is safe in AN, and may be useful in addressing some core domains of AN pathology. Other targets may also be worth studying in this population, in future sham-controlled trials with larger sample sizes. TRIAL REGISTRATION: Trial registration ClinicalTrials.gov NCT04409704 . Registered May 282,020. Retrospectively registered.

Anorexia nervosa is a serious illness that is difficult to treat. New treatments are urgently needed. This paper describes a preliminary study of a potential new treatment for Anorexia Nervosa, transcranial magnetic stimulation. In this treatment a magnetic field is generated and applied from outside the skull to affect specific areas of the brain thought to be involved in Anorexia nervosa. The results of this preliminary trial, conducted with 19 subjects over 6 weeks, showed some improvements in the way people with Anorexia nervosa think about weight, shape and their eating. The benefits were associated with areas of the brain involved in decision making and in regulating emotions. These changes did not appear to be related to improvements in other conditions, such as depression.

Accelerated brain aging predicts impulsivity and symptom severity in depression.

Multiple structural and functional neuroimaging measures vary over the course of the lifespan and can be used to predict chronological age. Accelerated brain aging, as quantified by deviations in the MRI-based predicted age with respect to chronological age, is associated with risk for neurodegenerative conditions, bipolar disorder, and mortality. Whether age-related changes in resting-state functional connectivity are accelerated in major depressive disorder (MDD) is unknown, and, if so, it is unclear if these changes contribute to specific cognitive weaknesses that often occur in MDD. Here, we delineated age-related functional connectivity changes in a large sample of normal control subjects and tested whether brain aging is accelerated in MDD. Furthermore, we tested whether accelerated brain aging predicts individual differences in cognitive function. We trained a support vector regression model predicting age using resting-state functional connectivity in 710 healthy adults aged 18-89. We applied this model trained on normal aging subjects to a sample of actively depressed MDD participants (n = 109). The difference between predicted brain age and chronological age was 2.11 years greater (p = 0.015) in MDD patients compared to control participants. An older MDD brain age was significantly associated with increased impulsivity and, in males, increased depressive severity. Unexpectedly, accelerated brain aging was also associated with increased placebo response in a sham-controlled trial of high-frequency repetitive transcranial magnetic stimulation targeting the dorsomedial prefrontal cortex. Our results indicate that MDD is associated with accelerated brain aging, and that accelerated aging is selectively associated with greater impulsivity and depression severity.

Resting State Functional Connectivity and Outcomes of Psychotherapies for Late-Life Depression.

BACKGROUND: Problem solving therapy (PST) and "Engage," a reward-exposure" based therapy, are important treatment options for late-life depression, given modest efficacy of antidepressants in this disorder. Abnormal function of the reward and default mode networks has been observed during depressive episodes. This study examined whether resting state functional connectivity (rsFC) of reward and DMN circuitries is associated with treatment outcomes. METHODS: Thirty-two older adults with major depression (mean age = 72.7) were randomized to 9-weeks of either PST or "Engage." We assessed rsFC at baseline and week 6. We placed seeds in three a priori regions of interest: subgenual anterior cingulate cortex (sgACC), dorsal anterior cingulate cortex (dACC), and nucleus accumbens (NAcc). Outcome measures included the Hamilton Depression Rating Scale (HAMD) and the Behavioral Activation for Depression Scale (BADS). RESULTS: In both PST and "Engage," higher rsFC between the sgACC and middle temporal gyrus at baseline was associated with greater improvement in depression severity (HAMD). Preliminary findings suggested that in "Engage" treated participants, lower rsFC between the dACC and dorsomedial prefrontal cortex at baseline was associated with HAMD improvement. Finally, in Engage only, increased rsFC from baseline to week 6 between NAcc and Superior Parietal Cortex was associated with increased BADS scores. CONCLUSION: The results suggest that patients who present with higher rsFC between the sgACC and a structure within the DMN may benefit from behavioral psychotherapies for late life depression. "Engage" may lead to increased rsFC within the reward system reflecting a reconditioning of the reward systems by reward exposure.

Clinical, behavioral, and neural measures of reward processing correlate with escitalopram response in depression: a Canadian Biomarker Integration Network in Depression (CAN-BIND-1) Report.

Anhedonia is thought to reflect deficits in reward processing that are associated with abnormal activity in mesocorticolimbic brain regions. It is expressed clinically as a deficit in the interest or pleasure in daily activities. More severe anhedonia in major depressive disorder (MDD) is a negative predictor of antidepressant response. It is unknown, however, whether the pathophysiology of anhedonia represents a viable avenue for identifying biological markers of antidepressant treatment response. Therefore, this study aimed to examine the relationships between reward processing and response to antidepressant treatment using clinical, behavioral, and functional neuroimaging measures. Eighty-seven participants in the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) protocol received 8 weeks of open-label escitalopram. Clinical correlates of reward processing were assessed at baseline using validated scales to measure anhedonia, and a monetary incentive delay (MID) task during functional neuroimaging was completed at baseline and after 2 weeks of treatment. Response to escitalopram was associated with significantly lower self-reported deficits in reward processing at baseline. Activity during the reward anticipation, but not the reward consumption, phase of the MID task was correlated with clinical response to escitalopram at week 8. Early (baseline to week 2) increases in frontostriatal connectivity during reward anticipation significantly correlated with reduction in depressive symptoms after 8 weeks of treatment. Escitalopram response is associated with clinical and neuroimaging correlates of reward processing. These results represent an important contribution towards identifying and integrating biological, behavioral, and clinical correlates of treatment response. ClinicalTrials.gov: NCT01655706.

Dorsomedial prefrontal cortex repetitive transcranial magnetic stimulation for treatment-refractory major depressive disorder: A three-arm, blinded, randomized controlled trial.

BACKGROUND: Dorsomedial prefrontal cortex (DMPFC) repetitive transcranial magnetic stimulation (rTMS) is a novel intervention for treatment-refractory depression (TRD). To date, many open-label case series and one randomized controlled trial of modest sample size have provided preliminary evidence that DMPFC-rTMS is an effective treatment for TRD. Here, we report the results of a large, double-blinded, sham-controlled trial of DMPFC-rTMS for TRD. OBJECTIVE: The primary aim of this study was to determine the efficacy of DMPFC-rTMS for TRD under sham-controlled conditions. METHODS: 120 TRD patients were randomized to receive 30 twice-daily sessions of either active high-frequency, active low-frequency, or sham DMPFC-rTMS using a novel bent active/sham double-cone coil. Placebo stimulation also involved the use of surface electrodes placed above the eyebrows. The 17-item Hamilton Rating Scale for Depression served as the primary outcome measure. RESULTS: Although there was a significant main effect of treatment across all arms, active DMPFC-rTMS was not superior to sham. Both participants and assessors were unable to accuracy determine whether patients received active or placebo stimulation. However, technicians' treatment arm guesses were significantly above chance. CONCLUSION: DMPFC rTMS did not result in improvement of depressive symptoms greater than sham stimulation. We cannot rule out that the sham apparatus may also have elicited an antidepressant effect via electrical trigeminal stimulation; future DMPFC-rTMS trials are therefore warranted.

Intrinsic Brain Network Biomarkers of Antidepressant Response: a Review.

PURPOSE OF REVIEW: Poor treatment response is a hallmark of major depressive disorder. To tackle this problem, recent neuroimaging studies have sought to characterize antidepressant response in terms of pretreatment differences in intrinsic functional brain networks. Our aim is to review recent studies that predict antidepressant response using intrinsic network connectivity. We discuss current methodological limitations and directions for future antidepressant biomarker studies. RECENT FINDINGS: Functional connectivity stemming from the subgenual and rostral anterior cingulate has shown particular consistency in predicting antidepressant response. Differences in this connectivity may prove fruitful in differentiating treatment responders to many antidepressant interventions. Future biomarker studies should integrate biological MDD subtypes to address the disorder's inherent clinical heterogeneity. These clinical and scientific advancements have the potential to address this population marked by limited treatment response. Methodological considerations, including patient selection, response criteria, and model overfitting, will require future investigation to ensure that biomarkers generalize for prospective prediction of treatment response.

Corticostriatal Connectivity in Antisocial Personality Disorder by MAO-A Genotype and Its Relationship to Aggressive Behavior.

BACKGROUND: The influence of genetic variation on resting-state neural networks represents a burgeoning line of inquiry in psychiatric research. Monoamine oxidase A, an X-linked gene, is one example of a molecular target linked to brain activity in psychiatric illness. Monoamine oxidase A genetic variants, including the high and low variable nucleotide tandem repeat polymorphisms, have been shown to differentially affect brain functional connectivity in healthy humans. However, it is currently unknown whether these same polymorphisms influence resting-state brain activity in clinical conditions. Given its high burden on society and strong connection to violent behavior, antisocial personality disorder is a logical condition to study, since in vivo markers of monoamine oxidase A brain enzyme are reduced in key affect-modulating regions, and striatal levels of monoamine oxidase A show a relation with the functional connectivity of this same region. METHODS: We utilized monoamine oxidase A genotyping and seed-to-voxel-based functional connectivity to investigate the relationship between genotype and corticostriatal connectivity in 21 male participants with severe antisocial personality disorder and 19 male healthy controls. RESULTS: Dorsal striatal connectivity to the frontal pole and anterior cingulate gyrus differentiated antisocial personality disorder subjects and healthy controls by monoamine oxidase A genotype. Furthermore, the linear relationship of proactive aggression to superior ventral striatal-angular gyrus functional connectivity differed by monoamine oxidase A genotype in the antisocial personality disorder groups. CONCLUSIONS: These results suggest that monoamine oxidase A genotype may affect corticostriatal connectivity in antisocial personality disorder and that these functional connections may also underlie use of proactive aggression in a genotype-specific manner.

Abnormal Functional Connectivity of Frontopolar Subregions in Treatment-Nonresponsive Major Depressive Disorder.

BACKGROUND: Approximately 30% of patients with major depressive disorder develop treatment-nonresponsive depression (TNRD); novel interventions targeting the substrates of this illness population are desperately needed. Convergent evidence from lesion, stimulation, connectivity, and functional neuroimaging studies implicates the frontopolar cortex (FPC) as a particularly important region in TNRD pathophysiology; regions functionally connected to the FPC, once identified, could present favorable targets for novel brain stimulation treatments. METHODS: We recently published a parcellation of the FPC based on diffusion tensor imaging data, identifying distinct medial and lateral subregions. Here, we applied this parcellation to resting-state functional magnetic resonance imaging scans obtained in 56 patients with TNRD and 56 matched healthy control subjects. RESULTS: In patients, the medial FPC showed reduced connectivity to the anterior midcingulate cortex and insula. The left lateral FPC showed reduced connectivity to the right lateral orbitofrontal cortex and increased connectivity to the fusiform gyri. In addition, TNRD symptom severity correlated significantly with connectivity of the left lateral FPC subregion to a medial orbitofrontal cortex region of the classical reward network. CONCLUSIONS: Taken together, these findings suggest that changes in FPC subregion connectivity may underlie several dimensions of TNRD pathology, including changes in reward/positive valence, nonreward/negative valence, and cognitive control domains. Nodes of functional networks showing abnormal connectivity to the FPC could be useful in generating novel candidates for therapeutic brain stimulation in TNRD.