Heritability of cognitive and emotion processing during functional MRI in a twin sample.

Despite compelling evidence that brain structure is heritable, the evidence for the heritability of task-evoked brain function is less robust. Findings from previous studies are inconsistent possibly reflecting small samples and methodological variations. In a large national twin sample, we systematically evaluated heritability of task-evoked brain activity derived from functional magnetic resonance imaging. We used established standardised tasks to engage brain regions involved in cognitive and emotional functions. Heritability was evaluated across a conscious and nonconscious Facial Expressions of Emotion Task (FEET), selective attention Oddball Task, N-back task of working memory maintenance, and a Go-NoGo cognitive control task in a sample of Australian adult twins (N ranged from 136 to 226 participants depending on the task and pairs). Two methods for quantifying associations of heritability and brain activity were utilised; a multivariate independent component analysis (ICA) approach and a univariate brain region-of-interest (ROI) approach. Using ICA, we observed that a significant proportion of task-evoked brain activity was heritable, with estimates ranging from 23% to 26% for activity elicited by nonconscious facial emotion stimuli, 27% to 34% for N-back working memory maintenance and sustained attention, and 32% to 33% for selective attention in the Oddball task. Using the ROI approach, we found that activity of regions specifically implicated in emotion processing and selective attention showed significant heritability for three ROIs, including estimates of 33%-34% for the left and right amygdala in the nonconscious processing of sad faces and 29% in the medial superior prefrontal cortex for the Oddball task. Although both approaches show similar levels of heritability for the Nonconscious Faces and Oddball tasks, ICA results displayed a more extensive network of heritable brain function, including additional regions beyond the ROI analysis. Furthermore, multivariate twin modelling of both ICA networks and ROI activation suggested a mix of common genetic and unique environmental factors that contribute to the associations between networks/regions. Together, the results indicate a complex relationship between genetic factors and environmental interactions that ultimately give rise to neural activation underlying cognition and emotion.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials.

BACKGROUND: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. AIMS: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. METHOD: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. RESULTS: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, ßpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, ßpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (ßpooled = 0.16) and the IMD index (ßpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. CONCLUSIONS: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Oral ketamine effects on dynamics of functional network connectivity in patients treated for chronic suicidality.

The underlying brain mechanisms of ketamine in treating chronic suicidality and the characteristics of patients who will benefit from ketamine treatment remain unclear. To address these gaps, we investigated temporal variations of brain functional synchronisation in patients with suicidality treated with ketamine in a 6-week open-label oral ketamine trial. The trial's primary endpoint was the Beck Scale for Suicide Ideation (BSS). Patients who experienced greater than 50% improvement in BSS scores or had a BSS score less than 6 at the post-treatment and follow-up (10 weeks) visits were considered responders and persistent responders, respectively. The reoccurring and transient connectivity pattern (termed brain state) from 29 patients (45.6 years ± 14.5, 15 females) were investigated by dynamic functional connectivity analysis of resting-state functional MRI at the baseline, post-treatment, and follow-up. Post-treatment patients showed significantly more (FDR-Q = 0.03) transitions among whole brain states than at baseline. We also observed increased dwelling time (FDR-Q = 0.04) and frequency (FDR-Q = 0.04) of highly synchronised brain state at follow-up, which were significantly correlated with BSS scores (both FDR-Q = 0.008). At baseline, persistent responders had higher fractions (FDR-Q = 0.03, Cohen's d = 1.39) of a cognitive control network state with high connectivities than non-responders. These findings suggested that ketamine enhanced brain changes among different synchronisation patterns and enabled high synchronisation patterns in the long term, providing a possible biological pathway for its suicide-prevention effects. Moreover, differences in cognitive control states at baseline may be used for precise ketamine treatment planning.

Neuroimaging for precision medicine in psychiatry.

Although the lifetime burden due to mental disorders is increasing, we lack tools for more precise diagnosing and treating prevalent and disabling disorders such as major depressive disorder. We lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry, focusing on major depressive and anxiety disorders. We begin by outlining evidence for the use of functional neuroimaging to stratify the heterogeneity of these disorders, based on underlying circuit dysfunction. We then review the current landscape of how functional neuroimaging-derived circuit predictors can predict treatment outcomes and clinical trajectories in depression and anxiety. Future directions for advancing clinically appliable neuroimaging measures are considered. We conclude by considering the opportunities and challenges of translating neuroimaging measures into practice. As an illustration, we highlight one approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation.

Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation.

Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.

Transdiagnostic Mood, Anxiety, and Trauma Symptom Factors in Alcohol Use Disorder: Neural Correlates Across 3 Brain Networks.

BACKGROUND: Alcohol use disorder (AUD) is associated with high rates of trauma, mood, and anxiety disorders. Across these diagnoses, individual symptoms substantially overlap, highlighting the need for a transdiagnostic approach. Furthermore, there is limited research on how transdiagnostic psychopathology impacts the neural correlates of AUD. Thus, we aimed to identify symptom factors spanning diagnoses and examine how they relate to the neurocircuitry of addiction. METHODS: Eighty-six veterans with AUD completed self-report measures and reward, incentive salience, and cognitive control functional magnetic resonance imaging tasks. Factor analysis was performed on self-reported trauma, depression, anxiety, and stress symptoms to obtain transdiagnostic symptom compositions. Neural correlates of a priori-defined regions of interest in the 3 networks were assessed. Independent sample t tests were used to compare the same nodes by DSM-5 diagnosis. RESULTS: Four symptom factors were identified: Trauma distress, Negative affect, Hyperarousal, and Somatic anxiety. Trauma distress score was associated with increased cognitive control activity during response inhibition (dorsal anterior cingulate cortex). Negative affect was related to lower activation in reward regions (right caudate) but higher activation in cognitive control regions during response inhibition (left dorsolateral prefrontal cortex). Hyperarousal was related to lower reward activity during monetary reward anticipation (left caudate, right caudate). Somatic anxiety was not significantly associated with brain activation. No difference in neural activity was found by posttraumatic stress disorder, major depressive disorder, or generalized anxiety disorder diagnosis. CONCLUSIONS: These hypothesis-generating findings offer transdiagnostic symptom factors that are differentially associated with neural function and could guide us toward a brain-based classification of psychiatric dysfunction in AUD. Results warrant further investigation of transdiagnostic approaches in addiction.

Optimizing Antidepressant Efficacy: Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2 = 0.31; placebo: R2 = 0.22). Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel insights into the intricate neuropsychopharmacology of antidepressant treatment and paves the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

A pilot, randomized clinical trial: Left dorsolateral prefrontal cortex intermittent theta burst stimulation improves treatment outcomes in veterans with alcohol use disorder.

BACKGROUND: Transcranial magnetic stimulation (TMS) offers a promising treatment avenue to modulate brain function in alcohol use disorder (AUD). To the best of our knowledge, this pilot study is the first randomized, double-blind, sham-controlled trial to deliver intermittent theta burst stimulation to the left dorsolateral prefrontal cortex (DLPFC) among US veterans with AUD. We hypothesized that 20 sessions of real TMS are tolerable and feasible. As a secondary line of inquiry, we hypothesized that, relative to sham TMS, individuals receiving real TMS would experience greater reductions in 6-month relapse rates, anhedonia, and alcohol cue-reactivity. METHODS: Veterans (n = 17, one woman) were enrolled in a double-blind, sham-controlled trial (2-3 sessions/day; 7-10 days; 600 pulses/session; 20 sessions). Pre- and posttreatment assessments included responses to self-report questionnaires and functional magnetic resonance imaging measures of alcohol cue-reactivity. Alcohol consumption was assessed for 6 months. Linear mixed-effects models were constructed to predict posttreatment craving, mood, and cue-reactivity. RESULTS: Individuals who received active iTBS (n = 8) were less likely to relapse within 3 months after treatment than the sham-treated group (n = 9) (OR = 12.0). Greater reductions in anhedonia were observed following active iTBS (Cohen's d = -0.59), relative to sham (d = -0.25). Alcohol cue-reactivity was reduced following active iTBS and increased following sham within the left insula (d = -0.19 vs. 0.51), left thalamus (d = -0.28 vs. 0.77), right insula (d = 0.18 vs. 0.52), and right thalamus (d = -0.06 vs. 0.62). CONCLUSIONS: Relative to sham, we demonstrate that 20 sessions of real left DLPFC iTBS reduced the likelihood of relapse for at least 3 months. The potential utility of this approach is underscored by observed decreases in anhedonia and alcohol cue-reactivity-strong predictors of relapse among veterans. These initial data offer a valuable set of effect sizes to inform future clinical trials in this patient population.

Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety.

There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or 'biotypes' to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free (n = 801) and after randomization to pharmacotherapy or behavioral therapy (n = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry.