Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Panic disorder (PD) and agoraphobia (AG) are highly comorbid anxiety disorders with an increasing prevalence that have a significant clinical and public health impact but are not adequately recognized and treated. Although the current functional neuroimaging literature has documented a range of neural abnormalities in these disorders, primary studies are often not sufficiently powered and their findings have been inconsistent.

This meta-analysis aims to advance our understanding of the neural underpinnings of PD and AG by identifying the most robust patterns of differential neural activation that differentiate individuals diagnosed with one of or both these disorders from age-matched healthy controls.

We conducted a comprehensive literature search in the PubMed database for all peer-reviewed, whole-brain, task-based functional magnetic resonance imaging (fMRI) activation studies that compared adults diagnosed with PD and/or AG with age-matched healthy controls. Each of these articles was screened by two independent coding teams using formal inclusion criteria and according to current PRISMA guidelines. We then performed a voxelwise, whole-brain, meta-analytic comparison of PD/AG participants with age-matched healthy controls using multilevel kernel density analysis (MKDA) with ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias and 10,000 Monte Carlo simulations to correct for multiple comparisons.

With data from 34 primary studies and a substantial sample size (N=2138), PD/AG participants, relative to age-matched healthy controls, exhibited a reliable pattern of statistically significant, (p<.05-0.0001; FWE-corrected) abnormal neural activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

In this meta-analysis we found robust patterns of differential neural activation in participants diagnosed with PD/AG relative to age-matched healthy controls. These findings advance our understanding of the neural underpinnings of PD and AG and inform the development of brain-based clinical interventions such as non-invasive brain stimulation (NIBS) and treatment prediction and matching algorithms. Future studies should also investigate the neural similarities and differences between PD and AG to increase our understanding of possible differences in their etiology, diagnosis, and treatment.

None Declared

Bipolar I disorder (BD-I) is a chronic and recurrent mood disorder characterized by alternating episodes of depression and mania; it is also associated with substantial morbidity and mortality and with clinically significant functional impairments. While previous studies have used functional magnetic resonance imaging (fMRI) to examine neural abnormalities associated with BD-I, they have yielded mixed findings, perhaps due to differences in sampling and experimental design, including highly variable mood states at the time of scan.

The purpose of this study is to advance our understanding of the neural basis of BD-I and mania, as measured by fMRI activation studies, and to inform the development of more effective brain-based diagnostic systems and clinical treatments.

We conducted a large-scale meta-analysis of whole-brain fMRI activation studies that compared participants with BD-I, assessed during a manic episode, to age-matched healthy controls. Following PRISMA guidelines, we conducted a comprehensive PubMed literature search using two independent coding teams to evaluate primary studies according to pre-established inclusion criteria. We then used multilevel kernel density analysis (MKDA), a well-established, voxel-wise, whole-brain, meta-analytic approach, to quantitatively synthesize all qualifying primary fMRI activation studies of mania. We used ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias, and 10,000 Monte Carlo simulations to correct for multiple comparisons.

We found that participants with BD-I (N=2,042), during an active episode of mania and relative to age-matched healthy controls (N=1,764), exhibit a pattern of significantly (p<0.05-0.0001; FWE-corrected) different activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

This study supports the formulation of a robust neural basis for BD-I during manic episodes and advances our understanding of the pattern of abnormal activation in this disorder. These results may inform the development of novel brain-based clinical tools for bipolar disorder such as diagnostic biomarkers, non-invasive brain stimulation, and treatment-matching protocols. Future studies should compare the neural signatures of BD-I to other related disorders to facilitate the development of protocols for differential diagnosis and improve treatment outcomes in patients with BD-I.

None Declared

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent psychiatric condition that frequently originates in early development and is associated with a variety of functional impairments. Despite a large functional neuroimaging literature on ADHD, our understanding of the neural basis of this disorder remains limited, and existing primary studies on the topic include somewhat divergent results.

The present meta-analysis aims to advance our understanding of the neural basis of ADHD by identifying the most statistically robust patterns of abnormal neural activation throughout the whole-brain in individuals diagnosed with ADHD compared to age-matched healthy controls.

We conducted a meta-analysis of task-based functional magnetic resonance imaging (fMRI) activation studies of ADHD. This included, according to PRISMA guidelines, a comprehensive PubMed search and predetermined inclusion criteria as well as two independent coding teams who evaluated studies and included all task-based, whole-brain, fMRI activation studies that compared participants diagnosed with ADHD to age-matched healthy controls. We then performed multilevel kernel density analysis (MKDA) a well-established, whole-brain, voxelwise approach that quantitatively combines existing primary fMRI studies, with ensemble thresholding (p<0.05-0.0001) and multiple comparisons correction.

Participants diagnosed with ADHD (N=1,550), relative to age-matched healthy controls (N=1,340), exhibited statistically significant (p<0.05-0.0001; FWE-corrected) patterns of abnormal activation in multiple brains of the cerebral cortex and basal ganglia across a variety of cognitive control tasks.

This study advances our understanding of the neural basis of ADHD and may aid in the development of new brain-based clinical interventions as well as diagnostic tools and treatment matching protocols for patients with ADHD. Future studies should also investigate the similarities and differences in neural signatures between ADHD and other highly comorbid psychiatric disorders.

None Declared

Meta-analyses of functional magnetic resonance imaging (fMRI) studies have been used to elucidate the most reliable neural features associated with various psychiatric disorders. However, it has not been well-established whether each of these neural features is linked to a specific disorder or is transdiagnostic across multiple disorders and disorder categories, including mood, anxiety, and anxiety-related disorders.

This project aims to advance our understanding of the disorder-specific and transdiagnostic neural features associated with mood, anxiety, and anxiety-related disorders as well as to refine the methodology used to compare multiple disorders.

We conducted an exhaustive PubMed literature search followed by double-screening, double-extraction, and cross-checking to identify all whole-brain, case-control fMRI activation studies of mood, anxiety, and anxiety-related disorders in order to construct a large-scale meta-analytic database of primary studies of these disorders. We then employed multilevel kernel density analysis (MKDA) with Monte-Carlo simulations to correct for multiple comparisons as well as ensemble thresholding to reduce cluster size bias to analyze primary fMRI studies of mood, anxiety, and anxiety-related disorders followed by application of triple subtraction techniques and a second-order analysis to elucidate the disorder-specificity of the previously identified neural features.

We found that participants diagnosed with mood, anxiety, and anxiety-related disorders exhibited statistically significant (p < .05 – 0.0001; FWE-corrected) differences in neural activation relative to healthy controls throughout the cerebral cortex, limbic system, and basal ganglia. In addition, each of these psychiatric disorders exhibited a particular profile of neural features that ranged from disorder-specific, to category-specific, to transdiagnostic.

These findings indicate that psychiatric disorders exhibit a complex profile of neural features that vary in their disorder-specificity and can be detected with large-scale fMRI meta-analytic techniques. This approach has potential to fundamentally transform neuroimaging investigations of clinical disorders by providing a novel procedure for establishing disorder-specificity of observed results, which can be then used to advance our understanding of individual disorders as well as broader nosological issues related to diagnosis and classification of psychiatric disorders.

None Declared

Generalized anxiety disorder (GAD) is a highly prevalent mental illness that is associated with clinically significant distress, functional impairment, and poor emotional regulation. Primary functional magnetic resonance imaging (fMRI) studies of GAD report neural abnormalities in comparison to healthy controls. However, many of these findings in the primary literature are inconsistent, and it is unclear whether they are specific to GAD or shared transdiagnostically across related disorders.

This meta-analysis seeks to establish the most reliable neural abnormalities observed in individuals with GAD, as reported in the primary fMRI activation literature.

We conducted an exhaustive literature search in PubMed to identify primary studies that met our pre-specified inclusion criteria and then extracted relevant data from primary, whole-brain fMRI activation studies of GAD that reported coordinates in Talairach or MNI space. We then used multilevel kernel density analysis (MKDA) with ensemble thresholding to examine the differences between adults with GAD and healthy controls in order to identify brain regions that reached statistical significance across primary studies.

Patients with GAD showed statistically significant (α=0.05–0.0001; family-wise-error-rate corrected) neural activation in various regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

These results inform our understanding of the neural basis of GAD and are interpreted using a frontolimbic model of anxiety as well as specific clinical symptoms of this disorder and its relation to other mood and anxiety disorders. These results also suggest possible novel targets for emerging neurostimulation therapies (e.g., transcranial magnetic stimulation) and may be used to advance our understanding of the effects of current pharmaceutical treatments and ways to improve treatment selection and symptom-targeting for patients diagnosed with GAD.

None Declared

Functional magnetic resonance imaging (fMRI) has been used to identify the neural activity of both youth and adults diagnosed with major depressive disorder (MDD) in comparison to healthy age-matched controls. Previously reported abnormalities in depressed youth appear to mostly align with those found in depressed adults; however, some of the reported aberrant brain activity in youth has not been consistent with what is observed in adults, and to our knowledge there has not yet been a formal, quantitative comparison of these two groups. In addition, it is not known whether these observed differences between youth and adults with depression are attributable to developmental age or length-of-illness.

The aim of this study is to elucidate the similarities and differences in patterns of abnormal neural activity between adults and youth diagnosed with MDD and to then determine whether these observed differences are due to either developmental age or length-of-illness.

We used multilevel kernel density analysis (MKDA) with ensemble thresholding and triple subtraction to separately determine neural abnormalities throughout the whole brain in primary studies of depressed youth and depressed adults and then directly compare the observed abnormalities between each of those age groups. We then conducted further comparisons between multiple subgroups to control for age and length-of-illness and thereby determine the source of the observed differences between youth and adults with depression.

Adults and youth diagnosed with MDD demonstrated reliable, differential patterns of abnormal activation in various brain regions throughout the cerebral cortex that are statistically significant (p < .05; FWE-corrected). In addition, several of these brain regions that exhibited differential patterns of neural activation between the two age groups can be reliably attributed to either developmental age or length-of-illness.

These findings indicate that there are common and disparate patterns of brain activity between youth and adults with MDD, several of which can be reliably attributed to developmental age or length-of-illness. These results expand our understanding of the neural basis of depression across development and course of illness and may be used to inform the development of new, age-specific clinical treatments as well as prevention strategies for this disorder.

None Declared

Major depressive disorder (MDD) is a highly prevalent mental illness that frequently originates in early development and is pervasive during adolescence. Despite its high prevalence and early age of onset, our understanding of the potentially unique neural basis of MDD in this age group is still not well understood, and the existing primary literature on the topic includes many new and divergent results. This limited understanding of MDD in youth presents a critical need to further investigate its neural basis in youth and presents an opportunity to also improve clinical treatments that target its neural abnormalities.

The present study aims to advance our understanding of the neural basis of MDD in youth by identifying abnormal functional activation in various brain regions compared with healthy controls.

We conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies of MDD by using a well-established method, multilevel kernel density analysis (MKDA) with ensemble thresholding, to quantitatively combine all existing whole-brain fMRI studies of MDD in youth compared with healthy controls. This method involves a voxel-wise, whole-brain approach, that compares neural activation of patients with MDD to age-matched healthy controls across variations of task-based conditions, which we subcategorize into affective processing, executive functioning, positive valence, negative valence, and symptom provocation tasks.

Youth with MDD exhibited statistically significant (p<0.05; FWE-corrected) hyperactivation and hypoactivation in multiple brain regions compared with age-matched healthy controls. These results include significant effects that are stable across various tasks as well as some that appear to depend on task conditions.

This study strengthens our understanding of the neural basis of MDD in youth and may also be used to help identify possible similarities and differences between youth and adults with depression. It may also help inform the development of new treatment interventions and tools for predicting unique treatment responses in youth with depression.

None Declared

Curiosity toward the effects of psychedelic drugs on neural activation has increased due to their potential therapeutic benefits, particularly serotonergic psychedelics that act as 5-HT2A receptor agonists such as LSD, psilocybin, and MDMA. However, the pattern of their effects on neural activity in various brain regions in both clinical and healthy populations is still not well understood, and primary studies addressing this issue have sometimes generated inconsistent results.

The present meta-analysis aims to advance our understanding of the most widely used serotonergic psychedelics – LSD, psilocybin, and MDMA – by examining their effects on the functional activation throughout the whole brain among both clinical and healthy participants.

We conducted this meta-analysis by applying multilevel kernel density analysis (MKDA) with ensemble thresholding to quantitatively combine existing functional magnetic resonance imaging (fMRI) studies that examined whole-brain functional activation of clinical or healthy participants who were administered a serotonergic psychedelic.

Serotonergic psychedelics, including LSD, psilocybin, and MDMA, exhibited significant effects (α=0.05) on neural activation in several regions throughout the cerebral cortex and basal ganglia, including effects that may be common across and unique within each drug.

These observed effects of serotonergic psychedelics on neural activity advance our understanding of the functional neuroanatomy associated with their administration and may inform future studies of both their adverse and therapeutic effects, including emerging clinical applications for the treatment of several psychiatric disorders.

None Declared

Major depressive disorder (MDD) is a highly prevalent mental illness that often first occurs or persists into adulthood and is considered the leading cause of disability and disease burden worldwide. Unfortunately, individuals diagnosed with MDD who seek treatment often experience limited symptom relief and may not achieve long-term remission, which is due in part to our limited understanding of its underlying pathophysiology. Many studies that use task-based functional magnetic resonance imaging (fMRI) have found abnormal activation in brain regions in adults diagnosed with MDD, but those findings are often inconsistent; in addition, previous meta-analyses that quantitatively integrate this large body literature have found conflicting results.

This meta-analysis aims to advance our understanding of the neural basis of MDD in adults, as measured by fMRI activation studies, and address inconsistencies and discrepancies in the empirical literature.

We employed multilevel kernel density analysis (MKDA) with ensemble thresholding, a well-established method for voxel-wise, whole-brain meta-analyses, to conduct a quantitative comparison of all relevant primary fMRI activation studies of adult patients with MDD compared to age-matched healthy controls.

We found that adults with MDD exhibited a reliable pattern of statistically significant (p<0.05; FWE-corrected) hyperactivation and hypoactivation in several brain regions compared to age-matched healthy controls across a variety of experimental tasks.

This study supports previous findings that there is reliable neural basis of MDD that can be detected across heterogenous fMRI studies. These results can be used to inform development of promising treatments for MDD, including protocols for personalized interventions. They also provide the opportunity for additional studies to examine the specificity of these effects among various populations-of-interest, including youth vs. adults with depression as well as other related mood and anxiety disorders.

None Declared

Early administration of antibiotics in sepsis is associated with improved patient outcomes, but safe and generalizable approaches to de-escalate or discontinue antibiotics after suspected sepsis events are unknown.

We used a modified Delphi approach to identify safety criteria for an opt-out protocol to guide de-escalation or discontinuation of antibiotic therapy after 72 hours in non-ICU patients with suspected sepsis. An expert panel with expertise in antimicrobial stewardship and hospital epidemiology rated 48 unique criteria across 3 electronic survey rating tools. Criteria were rated primarily based on their impact on patient safety and feasibility for extraction from electronic health record review. The 48 unique criteria were rated by anonymous electronic survey tools, and the results were fed back to the expert panel participants. Consensus was achieved to either retain or remove each criterion.

After 3 rounds, 22 unique criteria remained as part of the opt-out safety checklist. These criteria included high-risk comorbidities, signs of severe illness, lack of cultures during sepsis work-up or antibiotic use prior to blood cultures, or ongoing signs and symptoms of infection.

The modified Delphi approach is a useful method to achieve expert-level consensus in the absence of evidence suifficient to provide validated guidance. The Delphi approach allowed for flexibility in development of an opt-out trial protocol for sepsis antibiotic de-escalation. The utility of this protocol should be evaluated in a randomized controlled trial.