Shared and unique heritability of hippocampal subregion volumes in children and adults.

Behavioral genetic analyses have not demonstrated robust, unique, genetic correlates of hippocampal subregion volume. Genetic differentiation of hippocampal longitudinal axis subregion volume has not yet been investigated in population-based samples, although this has been demonstrated in rodent and post-mortem human tissue work. The following study is the first population-based investigation of genetic factors that contribute to gray matter volume along the hippocampal longitudinal axis. Twin-based biometric analyses demonstrated that longitudinal axis subregions are associated with significant, unique, genetic variance, and that longitudinal axis subregions are also associated with significant shared, hippocampus-general, genetic factors. Our study's findings suggest that genetic differences in hippocampal longitudinal axis structure can be detected in individual differences in gray matter volume in population-level research designs.

Chronic chromosome instability induced by Plk1 results in immune suppression in breast cancer.

Chromosome instability (CIN) contributes to resistance to therapies and tumor evolution. Although natural killer (NK) cells can eliminate cells with complex karyotypes, high-CIN human tumors have an immunosuppressive phenotype. To understand which CIN-associated molecular features alter immune recognition during tumor evolution, we overexpress Polo-like kinase 1 (Plk1) in a Her2+ breast cancer model. These high-CIN tumors activate a senescence-associated secretory phenotype (SASP), upregulate PD-L1 and CD206, and induce non-cell-autonomous nuclear factor κB (NF-κß) signaling, facilitating immune evasion. Single-cell RNA sequencing from pre-neoplastic mammary glands unveiled the presence of Arg1+ macrophages, NK cells with reduced effector functions, and increased resting regulatory T cell infiltration. We further show that high PLK1-expressing human breast tumors display gene expression patterns associated with SASP, NF-κß signaling, and immune suppression. These findings underscore the need to understand the immune landscape in CIN tumors to identify more effective therapies, potentially combining immune checkpoint or NF-κß inhibitors with current treatments.

Precision functional MRI mapping reveals distinct connectivity patterns for depression associated with traumatic brain injury.

Depression associated with traumatic brain injury (TBI) is believed to be clinically distinct from primary major depressive disorder (MDD) and may be less responsive to conventional treatments. Brain connectivity differences between the dorsal attention network (DAN), default mode network (DMN), and subgenual cingulate have been implicated in TBI and MDD. To characterize these distinctions, we applied precision functional mapping of brain network connectivity to resting-state functional magnetic resonance imaging data from five published patient cohorts, four discovery cohorts (n = 93), and one replication cohort (n = 180). We identified a distinct brain connectivity profile in TBI-associated depression that was independent of TBI, MDD, posttraumatic stress disorder (PTSD), depression severity, and cohort. TBI-associated depression was independently associated with decreased DAN-subgenual cingulate connectivity, increased DAN-DMN connectivity, and the combined effect of both. This effect was stronger when using precision functional mapping relative to group-level network maps. Our results support the possibility of a physiologically distinct "TBI affective syndrome," which may benefit from individualized neuromodulation approaches to target its distinct neural circuitry.

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression.

At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test-retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. Thus, we sought to identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. We used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These "RSNM targets" were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region ("sgACC-derived targets"). The TBI-D cohort was also randomized to receive active (n = 9) or sham (n = 4) rTMS to RSNM targets with 20 daily sessions of sequential high-frequency left-sided stimulation and low-frequency right-sided stimulation. We found that the group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were thus identified based on DAN anti-correlation and DMN correlation. These RSNM targets showed greater test-retest reliability than sgACC-derived targets. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was also stronger and more reliable for RSNM-derived targets than for sgACC-derived targets. Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment also led to increased connectivity within and between the stimulation sites, the sgACC, and the DMN. Overall, these results suggest that RSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes.

Age-related differences in resting-state functional connectivity from childhood to adolescence.

The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.

Polygenic Risk for Schizophrenia, Major Depression, and Post-traumatic Stress Disorder and Hippocampal Subregion Volumes in Middle Childhood.

Studies demonstrate that individuals with diagnoses for Major Depressive Disorder (MDD), Post-traumatic Stress Disorder (PTSD), and Schizophrenia (SCZ) may exhibit smaller hippocampal gray matter relative to otherwise healthy controls, although the effect sizes vary in each disorder. Existing work suggests that hippocampal abnormalities in each disorder may be attributable to genetic liability and/or environmental variables. The following study uses baseline data from the Adolescent Brain and Cognitive Development[Formula: see text] Study (ABCD Study[Formula: see text]) to address three open questions regarding the relationship between genetic risk for each disorder and hippocampal volume reductions: (a) whether polygenic risk scores (PGRS) for MDD, PTSD, and SCZ are related to hippocampal volume; (b) whether PGRS for MDD, PTSD, and SCZ are differentially related to specific hippocampal subregions along the longitudinal axis; and (c) whether the association between PGRS for MDD, PTSD, and SCZ and hippocampal volume is moderated by sex and/or environmental adversity. In short, we did not find associations between PGRS for MDD, PTSD, and SCZ to be significantly related to any hippocampal subregion volumes. Furthermore, neither sex nor enviornmental adversity significantly moderated these associations. Our study provides an important null finding on the relationship genetic risk for MDD, PTSD, and SCZ to measures of hippocampal volume.

Family income buffers the relationship between childhood adverse experiences and putamen volume.

Adverse experiences and family income in childhood have been associated with altered brain development. While there is a large body of research examining these associations, it has primarily used cross-sectional data sources and studied adverse experiences and family income in isolation. However, it is possible that low family income and adverse experiences represent dissociable and potentially interacting profiles of risk. To address this gap in the literature, we examined brain structure as a function of adverse experiences in childhood and family income in 158 youths with up to five waves of MRI data. Specifically, we assessed the interactive effect of these two risk factors on six regions of interest: hippocampus, putamen, amygdala, nucleus accumbens, caudate, and thalamus. Adverse experiences and family income interacted to predict putamen volume (B = 0.086, p = 0.011) but only in participants with family income one standard deviation below the mean (slope estimate = -0.11, p = 0.03). These results suggest that adverse experiences in childhood result in distinct patterns of brain development across the socioeconomic gradient. Given previous findings implicating the role of the putamen in psychopathology-related behaviors, these results emphasize the importance of considering life events and socioeconomic context when evaluating markers of risk. Future research should include interactive effects of environmental exposures and family income to better characterize risk for psychopathology in diverse samples.

White matter alterations associated with lifetime and current depression in adolescents: Evidence for cingulum disruptions.

INTRODUCTION: Compared to research on adults with depression, relatively little work has examined white matter microstructure differences in depression arising earlier in life. Here we tested hypotheses about disruptions to white matter structure in adolescents with current and past depression, with an a priori focus on the cingulum bundles, uncinate fasciculi, corpus collosum, and superior longitudinal fasciculus. METHODS: One hundred thirty-one children from the Preschool Depression Study were assessed using a Human Connectome Project style diffusion imaging sequence which was processed with HCP pipelines and TRACULA to generate estimates of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). RESULTS: We found that reduced FA, reduced AD, and increased RD in the dorsal cingulum bundle were associated with a lifetime diagnosis of major depression and greater cumulative and current depression severity. Reduced FA, reduced AD, and increased RD in the ventral cingulum were associated with greater cumulative depression severity. CONCLUSION: These findings support the emergence of white matter differences detected in adolescence associated with earlier life and concurrent depression. They also highlight the importance of connections of the cingulate to other brain regions in association with depression, potentially relevant to understanding emotion dysregulation and functional connectivity differences in depression.

Developmental trajectories of cortical thickness by functional brain network: The roles of pubertal timing and socioeconomic status.

The human cerebral cortex undergoes considerable changes during development, with cortical maturation patterns reflecting regional heterogeneity that generally progresses in a posterior-to-anterior fashion. However, the organizing principles that govern cortical development remain unclear. In the current study, we characterized age-related differences in cortical thickness (CT) as a function of sex, pubertal timing, and two dissociable indices of socioeconomic status (i.e., income-to-needs and maternal education) in the context of functional brain network organization, using a cross-sectional sample (n = 789) diverse in race, ethnicity, and socioeconomic status from the Lifespan Human Connectome Project in Development (HCP-D). We found that CT generally followed a linear decline from 5 to 21 years of age, except for three functional networks that displayed nonlinear trajectories. We found no main effect of sex or age by sex interaction for any network. Earlier pubertal timing was associated with reduced mean CT and CT in seven networks. We also found a significant age by maternal education interaction for mean CT across cortex and CT in the dorsal attention network, where higher levels of maternal education were associated with steeper age-related decreases in CT. Taken together, our results suggest that these biological and environmental variations may impact the emerging functional connectome.

Preschool Depression and Hippocampal Volume: The Moderating Role of Family Income.

OBJECTIVE: Depression and low socioeconomic status have both been associated with hippocampal volume alterations. Whether these factors interact to predict neurobehavioral outcomes has not been adequately studied. The authors investigated family income as a moderator of the relationship between depression and hippocampal volume in a longitudinal sample. METHOD: Longitudinal behavioral data, beginning at preschool age, and behavioral and neuroimaging data from school age to adolescence were used to assess the impact of preschool only and total preschool to adolescent depression symptoms on hippocampal volumes using family income as a moderator (N = 176). RESULTS: Depression severity during the preschool period interacted with family income to predict hippocampal volumes at the intercept (ie, age 13 years; B = -0.078, p = .003). Interaction decomposition revealed that only individuals with relatively high family income exhibited smaller hippocampal volume with increasing depression severity (B = -0.146, p = .005). Family income was associated with hippocampus volumes only in individuals with low to moderate preschool depression severity (B = 0.289, p = .007 and B = 0.169, p = .030, respectively). CONCLUSION: Preschool depression severity interacts with family income to predict hippocampal volume across development, such that the effects of early depression are evident only in those with higher income. These findings suggest that hippocampal volume may not be an effective marker of risk for depression at different levels of socioeconomic status, and emphasizes the importance of the environmental context when assessing risk markers for depression. Future research should explore how socioeconomic stress may eclipse the effects of depression on hippocampal development, setting alternative neurodevelopmental risk trajectories.

Reproducible brain-wide association studies require thousands of individuals.

Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.

Early Childhood Socioeconomic Status and Cognitive and Adaptive Outcomes at the Transition to Adulthood: The Mediating Role of Gray Matter Development Across Five Scan Waves.

BACKGROUND: Early low socioeconomic status (SES) is associated with poor outcomes in childhood, many of which endure into adulthood. It is critical to determine how early low SES relates to trajectories of brain development and whether these mediate relationships to poor outcomes. We use data from a unique 17-year longitudinal study with five waves of structural brain imaging to prospectively examine relationships between preschool SES and cognitive, social, academic, and psychiatric outcomes in early adulthood. METHODS: Children (n = 216, 50% female, 47.2% non-White) were recruited from a study of early onset depression and followed approximately annually. Family income-to-needs ratios (SES) were assessed when children were ages 3 to 5 years. Volumes of cortical gray and white matter and subcortical gray matter collected across five scan waves were processed using the FreeSurfer Longitudinal pipeline. When youth were ages 16+ years, cognitive function was assessed using the NIH Toolbox, and psychiatric diagnoses, high-risk behaviors, educational function, and social function were assessed using clinician administered and parent/youth report measures. RESULTS: Lower preschool SES related to worse cognitive, high-risk, educational, and social outcomes (|standardized B| = 0.20-0.31, p values < .003). Lower SES was associated with overall lower cortical (standardized B = 0.12, p < .0001) and subcortical gray matter (standardized B = 0.17, p < .0001) volumes, as well as a shallower slope of subcortical gray matter growth over time (standardized B = 0.04, p = .012). Subcortical gray matter mediated the relationship of preschool SES to cognition and high-risk behaviors. CONCLUSIONS: These novel longitudinal data underscore the key role of brain development in understanding the long-lasting relations of early low SES to outcomes in children.

Associations of observed preschool performance monitoring with brain functional connectivity in adolescence.

Monitoring one's performance helps detect errors and adapt to prevent future mistakes. However, elevated performance monitoring is associated with increased checking behaviors and perfectionism and is characteristic of multiple psychiatric disorders. Understanding how heightened performance monitoring in early childhood relates to subsequent brain connectivity may elucidate mechanistic risk factors that influence brain and psychiatric outcomes. The aim of this study was to examine the association between performance monitoring in preschool-aged children and functional connectivity during adolescence. In the current prospective longitudinal study, we performed seed-based functional connectivity analysis using a dorsal anterior cingulate cortex (dACC) seed to assess brain-behavior relationships between observationally coded performance monitoring in preschool-aged children and adolescent functional connectivity (n = 79). We also utilized enrichment analysis to investigate network-level connectome-wide associations. Seed-based analysis revealed negative correlations between preschool performance monitoring and adolescent fc between dACC and orbitofrontal and dorsolateral prefrontal cortex while a positive correlation was observed between dACC-occipital cortex connectivity. Enrichment analysis revealed a negative correlation between preschool performance monitoring and connectivity between motor (MOT) - cingulo-opercular (CO) and salience (SN) - Reward (REW) and a positive correlation with MOT-DMN, and cerebellum (CB) - motor connectivity. Elevated performance monitoring in early childhood is associated with functional connectivity during adolescence in regions and networks associated with cognitive control, sensorimotor processing and cortico-striatal-thalamic-cortico (CTSC) aberrations. These regions and networks are implicated in psychiatric disorders characterized by elevated performance monitoring. Findings shed light on a mechanistic risk factor in early childhood with long-term associations with neural functioning.

Amygdala Activation in Cognitive Task fMRI Varies with Individual Differences in Cognitive Traits.

The amygdala has been implicated in processing threat and learning fear. However, the amygdala also responds to motivationally relevant stimuli even in the absence of explicit emotional content. We investigated the relationship among amygdala activation, cognitive and emotional factors, and fMRI task data in participants from the Young Adult Human Connectome Project. We expected to see variation in amygdala activation that corresponded with variation in traits that could affect the salience of task related stimuli (i.e., internalizing symptoms and fearful faces). We found no relationship between amygdala activation during face viewing and emotion related traits. However, amygdala activation under working memory load was negatively correlated with fluid intelligence and reading level. There also was a negative relationship between task performance and activation in the amygdala. The observed relationship suggests that the role of amygdala is not limited to the processing of emotional content of incoming information but is instead related to salience, which can be influenced by individual differences.

Examining Specificity of Neural Correlates of Childhood Psychotic-like Experiences During an Emotional n-Back Task.

BACKGROUND: Psychotic-like experiences (PLEs) during childhood are associated with greater risk of developing a psychotic disorder in adulthood, highlighting the importance of identifying neural correlates of childhood PLEs. Furthermore, impairment of cognitive functions, such as working memory and emotion regulation, has also been linked to psychosis risk as well as to disruptions in several brain regions. However, impairments in these domains have also been linked to other disorders, including depression. Therefore, the aim of the current study was to examine whether neural impairments in regions associated with working memory and implicit emotion regulation impairments are specific to PLEs versus depression. METHODS: The current study used an emotional n-back task to examine the relationship between childhood PLEs and neural activation of regions involved in both working memory and implicit emotion regulation using data from 8805 9- to 11-year-olds in the Adolescent Brain Cognitive Development (ABCD) Study 2.0 release. To examine specificity, we also analyzed associations with depressive symptoms. RESULTS: Our results indicated that increased PLEs during middle childhood were associated with decreased activation of the dorsolateral prefrontal cortex, striatum, and pallidum during trials requiring working memory. In contrast, increased activation of the parahippocampus, caudate, nucleus accumbens, and rostral anterior cingulate during face-viewing trials was associated with increased depressive symptoms. CONCLUSIONS: These results support the dimensional view of psychosis across the lifespan, providing evidence that neural correlates of PLEs, such as decreased activation during working memory, are present during middle childhood. Furthermore, these correlates are specific to psychotic-like symptoms as compared with depressive symptoms.

Brain Reward System Dysfunction in Adolescence: Current, Cumulative, and Developmental Periods of Depression.

OBJECTIVE: Reward system dysfunction is a well-known correlate and predictor of depression in adults and adolescents, with depressed individuals showing blunted (hyporeactive) striatal response to monetary rewards. Furthermore, studies of remitted depression suggest network-wide hyporeactivity of striatal (caudate, putamen, nucleus accumbens) and cortical (insula, anterior cingulate cortex [ACC]) regions even in the absence of current symptoms. Thus, it remains unclear which patterns of hyporeactivity represent a trait-like indicator of depression and which represent a current depressed state. The authors examined the relationships between regions of a cortico-striatal circuit supporting reward processing and both current depression and cumulative depression history. METHODS: Using a functional MRI monetary reward task, the authors measured brain response to monetary gains and losses in a longitudinal sample of adolescents (N=131) who had been annually assessed for psychiatric symptoms since ages 3-5 years. RESULTS: Current depression severity was associated with hyporeactivity exclusively in the nucleus accumbens in response to the anticipation of a reward, while cumulative depression severity was associated with blunted response to anticipation across a cortico-striatal circuit (striatum, ACC, insula). Follow-up analyses investigating the effects of depression on reward processing at different developmental stages revealed a similar pattern: recent depression severity during adolescence was associated with more focal hyporeactivity in the nucleus accumbens, while depression severity during early childhood (i.e., preschool) was associated with more global hyporeactivity across the cortico-striatal circuit. CONCLUSIONS: The study findings indicate important distinctions between disruptions in reward system neural circuitry associated with a history of depression (particularly early-onset depression) and current depression. These results have implications for understanding the etiology and treatment of reward processing deficits in depression.

Acquisition of chromosome instability is a mechanism to evade oncogene addiction.

Chromosome instability (CIN) has been associated with therapeutic resistance in many cancers. However, whether tumours become genomically unstable as an evolutionary mechanism to overcome the bottleneck exerted by therapy is not clear. Using a CIN model of Kras-driven breast cancer, we demonstrate that aneuploid tumours acquire genetic modifications that facilitate the development of resistance to targeted therapy faster than euploid tumours. We further show that the few initially chromosomally stable cancers that manage to persist during treatment do so concomitantly with the acquisition of CIN. Whole-genome sequencing analysis revealed that the most predominant genetic alteration in resistant tumours, originated from either euploid or aneuploid primary tumours, was an amplification on chromosome 6 containing the cMet oncogene. We further show that these tumours are dependent on cMet since its pharmacological inhibition leads to reduced growth and increased cell death. Our results highlight that irrespective of the initial CIN levels, cancer genomes are dynamic and the acquisition of a certain level of CIN, either induced or spontaneous, is a mechanism to circumvent oncogene addiction.

Development of Network Topology and Functional Connectivity of the Prefrontal Cortex.

The prefrontal cortex (PFC) comprises distinct regions and networks that vary in their trajectories across development. Further understanding these diverging trajectories may elucidate the neural mechanisms by which distinct PFC regions contribute to cognitive maturity. In particular, it remains unclear whether PFC regions of distinct network affiliations differ in topology and their relationship to cognition. We examined 615 individuals (8-21 years) to characterize age-related effects in participation coefficient of 28 PFC regions of distinct networks, evaluating connectivity profiles of each region to understand patterns influencing topological maturity. Findings revealed that PFC regions of attention, frontoparietal, and default mode networks (DMN) displayed varying rates of decline in participation coefficient with age, characterized by stronger connectivity with each PFC's respective network; suggesting that PFC regions largely aid network segregation. Conversely, PFC regions of the cinguloopercular/salience network increased in participation coefficient with age, marked by stronger between-network connections, suggesting that some PFC regions feature a distinctive ability to facilitate network integration. PFC topology of the DMN, in particular, predicted improvements in global cognition, including motor speed and higher order abilities. Together, these findings elucidate systematic differences in topology across PFC regions of different network affiliation, representing important neural signatures of typical brain development.