Neurocognitive and functional heterogeneity in depressed youth

Neuroanatomical subtypes of tobacco use disorder and relationship with clinical and molecular features

BACKGROUND

Individual neurobiological heterogeneity among patients with tobacco use disorder (TUD) hampers the identification of neuroimaging phenotypes.

METHODS

The current study recruited 122 TUD individuals and 57 healthy controls, and obtained their 3D-T1 images. Heterogeneity through discriminative analysis (HYDRA) was applied to uncover the potential subtype of TUD where regional gray matter volume (GMV) was treated as the feature. Then we examined the clinical, neuroimaging and molecular characteristics of subtypes.

RESULTS

Two distinct neuroanatomical subtypes were found. In subtype 1, TUD individuals showed decreased GMV in right orbitofrontal cortex (OFC), while subtype 2 exhibited distributed pattern of widely GMV increase. Moreover, subtype 1 showed older initial smoking age, longer duration of smoking than Subtype 2. Persistent smoking behavior in subtype 1 is more likely caused by substance dependence/addiction rather than psychosocial factors. GMV correlated negatively with cumulative tobacco exposure in Subtype 1 but not in Subtype 2. Besides, neuroanatomical aberrance in subtype 1 was mainly associated with dopamine system, while neuroanatomical abnormalities in subtype 2 were primarily associated with GABAa.

CONCLUSIONS

Overall, our results revealed two opposite neuroanatomical subtypes of TUD, which largely overlapped with their clinical and molecular features respectively. TUD subtypes taxonomy based on objective anatomy could help to facilitate the development of individualized treatment for TUD.

Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11.2 deletion syndrome

BACKGROUND

Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in-person assessment can be unavailable or burdensome. The current study compares in-person and remote assessments of the Penn computerised neurocognitive battery (CNB).

METHODS

Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in-person at a laboratory (n = 222) or remotely (n = 162).

RESULTS

Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks.

CONCLUSIONS

These findings suggest that the CNB can be used in remote settings to assess multiple neurocognitive domains.

Assessment of memory deficits in psychiatric disorders: A systematic literature review

Memory deficits are observed across psychiatric disorders ranging from the prodrome of psychosis to common mental disorders such as anxiety, depression, and dissociative disorders. Memory deficits among patients recovering from psychiatric disorders could be directly related to the primary illness or secondary to the adverse effect of a treatment such as Electroconvulsive Therapy (ECT). The trouble in the meaningful integration of working-memory and episodic memory is the most commonly affected domain that requires routine assessments. An update on the recent trends of methods of assessment of memory deficits is the first step towards understanding and correcting these deficits to target optimum recovery. A systematic literature search was conducted from October 2018 to October 2022 to review the recent methods of assessment of memory deficits in psychiatric disorders. The definition of 'Memory deficit' was operationalized as 'selective processes of memory, commonly required for activities of daily living, and affected among psychiatric disorders resulting in subjective distress and dysfunction'. We included 110 studies, most of them being conducted in western countries on patients with schizophrenia. Other disorders included dementia and mild cognitive impairment. Brief Assessment of Cognition in Schizophrenia, Cambridge Automated Neuropsychological Test Battery, California Verbal Learning Test, Trail Making Test Part A and B, Rey Auditory Verbal Learning Test, Wechsler Memory Scale, Wechsler Adults Intelligence Scale-IV were the most common neuropsychological assessments used. Mini-Mental State Examination and Montreal Cognitive Assessment were the most common bedside assessment tools used while Squire Subjective Memory Questionnaire was commonly used to measure ECT-related memory deficits. The review highlights the recent developments in the field of assessment of memory deficits in psychiatric disorders. Findings recommend and emphasize routine assessment of memory deficits among psychiatric disorders in developing countries especially severe mental illnesses. It remains interesting to see the role of standardized assessments in diagnostic systems given more than a decade of research on memory deficits in psychiatric disorders.

Revealing complexity: segmentation of hippocampal subfields in adolescents with major depressive disorder reveals specific links to cognitive dysfunctions

BACKGROUND

Hippocampal disruptions represent potential neuropathological biomarkers in depressed adolescents with cognitive dysfunctions. Given heterogeneous outcomes of whole-hippocampus analyses, we investigated subregional abnormalities in depressed adolescents and their associations with symptom severity and cognitive dysfunctions.

METHODS

MethodsSeventy-nine first-episode depressive patients (ag = 15.54 ± 1.83) and 71 healthy controls (age = 16.18 ± 2.85) were included. All participants underwent T1 and T2 imaging, completed depressive severity assessments, and performed cognitive assessments on memory, emotional recognition, cognitive control, and attention. Freesurfer was used to segment each hippocampus into 12 subfields. Multivariable analyses of variance were performed to identify overall and disease severity-related abnormalities in patients. LASSO regression was also conducted to explore the associations between hippocampal subfields and patients' cognitive abilities.

RESULTS

Depressed adolescents showed decreases in dentate gyrus, CA1, CA2/3, CA4, fimbria, tail, and molecular layer. Analyses of overall symptom severity, duration, self-harm behavior, and suicidality suggested that severity-related decreases mainly manifested in CA regions and involved surrounding subfields with disease severity increases. LASSO regression indicated that hippocampal subfield abnormalities had the strongest associations with memory impairments, with CA regions and dentate gyrus showing the highest weights.

CONCLUSIONS

Hippocampal abnormalities are widespread in depressed adolescents and such abnormalities may spread from CA regions to surrounding areas as the disease progresses. Abnormalities in CA regions and dentate gyrus among these subfields primarily link with memory impairments in patients. These results demonstrate that hippocampal subsections may serve as useful biomarkers of depression progression in adolescents, offering new directions for early clinical intervention.

Cognitive functioning in children and adolescents with depression: A systematic review and meta-analysis

Although cognitive dysfunction is associated with depression in adults, the link in children and adolescents is unclear. This systematic review and meta-analysis quantifies the association between depression and cognitive function in children and adolescents. Systematic searches were conducted in six databases: Child Development and Adolescent Studies, Ovid MEDLINE, Ovid Embase, Ovid APA PsycINFO, EBSCO CINAHL Plus, Scopus (last search: April 2023). Studies including measures of cognitive outcomes (memory, attention, executive function, processing speed, language) among children (≤18 years) with depression were included. The Joanna Briggs Institute Critical Appraisal Tools were used to determine study risk of bias. Random-effects meta-analyses of study outcomes were performed. Seventeen studies were included (15 were cross-sectional, 1 prospective, 1 randomized control trial). Participants (N = 13,567) were 10 to 17 years old (mean 13.8 ± 2.2 years; 60 % female). Compared with healthy controls, depressed participants had lower performance on tests of working memory (g = -0.40; 95 % CI: -0.67, -0.13), long-term memory (g = -0.48; 95 % CI: -0.72, -0.25), attention (g = -0.15; 95 % CI: -0.26, -0.04), executive function (g = -0.16; 95 % CI: -0.24, -0.08), and language (g = -0.23; 95 % CI: -0.36, -0.09). No performance differences were observed on tests of short-term memory or processing speed. Children and adolescents with depression demonstrated lower performance on tests of working and long-term memory, attention, executive function and language. These findings emphasize the importance of considering cognitive functioning among children with depression, and greater understanding of the effect of treatment on these outcomes. PROSPERO (CRD42022332064).

Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering

BACKGROUND

Similarities among schizophrenia (SZ), schizoaffective disorder (SAD) and bipolar disorder (BP) including clinical phenotypes, brain alterations and risk genes, make it challenging to perform reliable separation among them. However, previous subtype identification that transcend traditional diagnostic boundaries were based on group-level neuroimaging features, ignoring individual-level inferences.

METHODS

455 psychoses (178 SZs, 134 SADs and 143 BPs), their first-degree relatives (N = 453) and healthy controls (HCs, N = 220) were collected from Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP I) consortium. Individualized covariance structural differential networks (ICSDNs) were constructed for each patient and multi-site clustering was used to identify psychosis subtypes. Group differences between subtypes in clinical phenotypes and voxel-wise fractional amplitude of low frequency fluctuation (fALFF) were calculated, as well as between the corresponding relatives.

RESULTS

Two psychosis subtypes were identified with increased whole brain structural covariance, with decreased connectivity between amygdala-hippocampus and temporal-occipital cortex in subtype I (S-I) compared to subtype II (S-II), which was replicated under different clustering methods, number of edges and across datasets (B-SNIP II) and different brain atlases. S-I had higher emotional-related symptoms than S-II and showed significant fALFF decrease in temporal and occipital cortex, while S-II was more similar to HC. This pattern was consistently validated on relatives of S-I and S-II in both fALFF and clinical symptoms.

CONCLUSIONS

These findings reconcile categorical and dimensional perspectives of psychosis neurobiological heterogeneity, indicating that relatives of S-I might have greater predisposition in developing psychosis, while relatives of S-II are more likely to be healthy. This study contributes to the development of neuroimaging informed diagnostic classifications within psychosis spectrum.

Distinct neurocognitive profiles and clinical phenotypes associated with copy number variation at the 22q11.2 locus

Rare genetic variants that confer large effects on neurodevelopment and behavioral phenotypes can reveal novel gene-brain-behavior relationships relevant to autism. Copy number variation at the 22q11.2 locus offer one compelling example, as both the 22q11.2 deletion (22qDel) and duplication (22qDup) confer increased likelihood of autism spectrum disorders (ASD) and cognitive deficits, but only 22qDel confers increased psychosis risk. Here, we used the Penn Computerized Neurocognitive Battery (Penn-CNB) to characterized neurocognitive profiles of 126 individuals: 55 22qDel carriers (MAge  = 19.2 years, 49.1% male), 30 22qDup carriers (MAge  = 17.3 years, 53.3% male), and 41 typically developing (TD) subjects (MAge  = 17.3 years, 39.0% male). We performed linear mixed models to assess group differences in overall neurocognitive profiles, domain scores, and individual test scores. We found all three groups exhibited distinct overall neurocognitive profiles. 22qDel and 22qDup carriers showed significant accuracy deficits across all domains relative to controls (episodic memory, executive function, complex cognition, social cognition, and sensorimotor speed), with 22qDel carriers exhibiting more severe accuracy deficits, particularly in episodic memory. However, 22qDup carriers generally showed greater slowing than 22qDel carriers. Notably, slower social cognition speed was uniquely associated with increased global psychopathology and poorer psychosocial functioning in 22qDup. Compared to TD, 22q11.2 copy number variants (CNV) carriers failed to show age-associated improvements in multiple cognitive domains. Exploratory analyses revealed 22q11.2 CNV carriers with ASD exhibited differential neurocognitive profiles, based on 22q11.2 copy number. These results suggest that there are distinct neurocognitive profiles associated with either a loss or gain of genomic material at the 22q11.2 locus.

Mapping the relationship of white matter lesions to depression in multiple sclerosis

Importance

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects nearly one million people in the United States. Up to 50% of patients with MS experience depression.

Objective

To investigate how white matter network disruption is related to depression in MS.

Design

Retrospective case-control study of participants who received research-quality 3-tesla neuroimaging as part of MS clinical care from 2010-2018. Analyses were performed from May 1 to September 30, 2022.

Setting

Single-center academic medical specialty MS clinic.

Participants

Participants with MS were identified via the electronic health record (EHR). All participants were diagnosed by an MS specialist and completed research-quality MRI at 3T. After excluding participants with poor image quality, 783 were included. Inclusion in the depression group (MS+Depression) required either: 1) ICD-10 depression diagnosis (F32-F34.*); 2) prescription of antidepressant medication; or 3) screening positive via Patient Health Questionnaire-2 (PHQ-2) or -9 (PHQ-9). Age- and sex-matched nondepressed comparators (MS-Depression) included persons with no depression diagnosis, no psychiatric medications, and were asymptomatic on PHQ-2/9.

Exposure

Depression diagnosis.

Main Outcomes and Measures

We first evaluated if lesions were preferentially located within the depression network compared to other brain regions. Next, we examined if MS+Depression patients had greater lesion burden, and if this was driven by lesions specifically in the depression network. Outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain. Secondary measures included between-diagnosis lesion burden, stratified by brain network. Linear mixed-effects models were employed.

Results

Three hundred-eighty participants met inclusion criteria, (232 MS+Depression: age[SD]=49[12], %females=86; 148 MS-Depression: age[SD]=47[13], %females=79). MS lesions preferentially affected fascicles within versus outside the depression network (β=0.09, 95% CI=0.08-0.10, P<0.001). MS+Depression had more white matter lesion burden (β=0.06, 95% CI=0.01-0.10, P=0.015); this was driven by lesions within the depression network (β=0.02, 95% CI 0.003-0.040, P=0.020).

Conclusions and Relevance

We provide new evidence supporting a relationship between white matter lesions and depression in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression had more disease than MS-Depression, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Leveraging Machine Learning for Gaining Neurobiological and Nosological Insights in Psychiatric Research

Much attention is currently devoted to developing diagnostic classifiers for mental disorders. Complementing these efforts, we highlight the potential of machine learning to gain biological insights into the psychopathology and nosology of mental disorders. Studies to this end have mainly used brain imaging data, which can be obtained noninvasively from large cohorts and have repeatedly been argued to reveal potentially intermediate phenotypes. This may become particularly relevant in light of recent efforts to identify magnetic resonance imaging-derived biomarkers that yield insight into pathophysiological processes as well as to refine the taxonomy of mental illness. In particular, the accuracy of machine learning models may be used as dependent variables to identify features relevant to pathophysiology. Moreover, such approaches may help disentangle the dimensional (within diagnosis) and often overlapping (across diagnoses) symptomatology of psychiatric illness. We also point out a multiview perspective that combines data from different sources, bridging molecular and system-level information. Finally, we summarize recent efforts toward a data-driven definition of subtypes or disease entities through unsupervised and semisupervised approaches. The latter, blending unsupervised and supervised concepts, may represent a particularly promising avenue toward dissecting heterogeneous categories. Finally, we raise several technical and conceptual aspects related to the reviewed approaches. In particular, we discuss common pitfalls pertaining to flawed input data or analytic procedures that would likely lead to unreliable outputs.

Controversies In The Pharmacotherapy Of Adolescent Depression

BACKGROUND

Although fluoxetine and, in the USA, escitalopram are approved for depression in adolescence, substantial concern surrounds antidepressant use in youth. Major controversies regarding efficacy and safety (increased suicidality).

INTRODUCTION

The cathegory of depression is very broad and overinclusive, in terms of etiology, role of psychosocial adversities severity, episodicity, presentation, relationship with bipolarity. This heterogeneity, not fully controlled considered in Randomized Controlled Trials (RCTs), may account for the disappointing results on both efficacy and safety.

METHOD

Based on the available literature, we will address the following topics: a) controversies regarding the definition of depression as a unique homogeneous condition with a unique type of pharmacological treatment; b) controversies about the interpretation of data from Randomized Controlled Trials (RCTs) on the efficacy of pharmacological treatments in adolescent depression; c) the interpretation of data regarding the safety of antidepressant treatment in adolescent depression, particularly in terms of increased suicidal risk.

RESULTS

According to RCTs, antidepressants are minimally to moderately more effective than placebo, principally based on very high placebo responses, and only fluoxetine showed more evidence of efficacy. These differences in meta-analyses are sometimes statistically, but not clinically significant. Depression is a heterogeneous condition in terms of etiology, role of psychosocial adversities severity, episodicity, presentation, relationship with bipolarity. This heterogeneity may partly explain the low drug-placebo difference and the high placebo response (possibly related to a high level of natural recovery of the adolescent depression). In the National Institute of Mental Health (NIMH)-funded studies, including a lower number of study sites and more reliable enrollment procedures, lower placebo response rates and greater group differences between medication and placebo were found. Robust evidence supports an increased risk of emergent suicidality after starting antidepressants. A clear age effect on suicidal risk after antidepressants is supported by a comprehensive meta-analysis, showing that suicidal risk increased with decreasing age, being markedly greater in subjects aged between 18 and 25 years. However, the term suicidality is too broad, as it includes suicidal ideation, suicidal attempts, and completed suicide, with a hugely wide range of severity and pervasiveness. If emergent suicidality should be actively and carefully explored, empirical evidence, albeit weak, suggests that combined pharmacotherapy (antidepressant and/or lithium) associated with psychotherapy may be helpful in reducing pretreatment suicidal ideation and suicidal risk.

DISCUSSION

Moderate to severe depression should be treated with psychotherapy and/or fluoxetine, the best-supported medication, and treatment-resistant adolescents should always receive combined treatment with psychotherapy. Suicidal ideation, particularly with a plan, should be actively explored before starting an antidepressant, as a reason for the closest monitoring. Emergent suicidality after starting antidepressants, as well as antidepressant-related activation, should also be closely monitored and may lead to antidepressant discontinuation. Although no response to pharmacotherapy and psychotherapy may occur in up to 40% of depressed adolescents, possible predictors or mediators of poorer response in adolescents are uncertain, and only a few studies support possible treatment strategies. Finally, studies exploring the efficacy of antidepressants in specific depression subtypes, i.e., based on prevalent psychopathological dimensions (apathy, withdrawal, impulsivity), are warranted.

Developmental coupling of cerebral blood flow and fMRI fluctuations in youth

The functions of the human brain are metabolically expensive and reliant on coupling between cerebral blood flow (CBF) and neural activity, yet how this coupling evolves over development remains unexplored. Here, we examine the relationship between CBF, measured by arterial spin labeling, and the amplitude of low-frequency fluctuations (ALFF) from resting-state magnetic resonance imaging across a sample of 831 children (478 females, aged 8-22 years) from the Philadelphia Neurodevelopmental Cohort. We first use locally weighted regressions on the cortical surface to quantify CBF-ALFF coupling. We relate coupling to age, sex, and executive functioning with generalized additive models and assess network enrichment via spin testing. We demonstrate regionally specific changes in coupling over age and show that variations in coupling are related to biological sex and executive function. Our results highlight the importance of CBF-ALFF coupling throughout development; we discuss its potential as a future target for the study of neuropsychiatric diseases.

Effects and Mechanisms of Synaptotagmin-7 in the Hippocampus on Cognitive Impairment in Aging Mice

Aging is an irreversible biological process that involves oxidative stress, neuroinflammation, and apoptosis, and eventually leads to cognitive dysfunction. However, the underlying mechanisms are not fully understood. In this study, we investigated the role and potential mechanisms of Synaptotagmin-7, a calcium membrane transporter in cognitive impairment in aging mice. Our results indicated that Synaptotagmin-7 expression significantly decreased in the hippocampus of D-galactose-induced or naturally aging mice when compared with healthy controls, as detected by western blot and quantitative reverse transcriptase-polymerase chain reaction analysis. Synaptotagmin-7 overexpression in the dorsal CA1 of the hippocampus reversed long-term potentiation and improved hippocampus-dependent spatial learning in D-galactose-induced aging mice. Synaptotagmin-7 overexpression also led to fully preserved learning and memory in 6-month-old mice. Mechanistically, we demonstrated that Synaptotagmin-7 improved learning and memory by elevating the level of fEPSP and downregulating the expression of aging-related genes such as p53 and p16. The results of our study provide new insights into the role of Synaptotagmin-7 in improving neuronal function and overcoming memory impairment caused by aging, suggesting that Synaptotagmin-7 overexpression may be an innovative therapeutic strategy for treating cognitive impairment.