Cellular correlates of cortical thinning throughout the lifespan

Dynamic Structural Brain Changes in Anorexia Nervosa: A Replication Study, Mega-analysis, and Virtual Histology Approach

OBJECTIVE

Several, but not all, previous studies of brain structure in anorexia nervosa (AN) have reported reductions in gray matter volume and cortical thickness (CT) in acutely underweight patients, which seem to reverse upon weight gain. The biological mechanisms underlying these dynamic alterations remain unclear.

METHOD

In this structural magnetic resonance imaging study, we first replicated and extended previous results in (1) a larger independent sample of 75 acutely underweight adolescent and young adult female patients with AN (acAN; n = 54 rescanned longitudinally after partial weight restoration), 34 weight-recovered individuals with a history of AN (recAN), and 139 healthy controls (HC); and 2) a greater combined sample compiled of both our previous samples and the present replication sample (120 acAN [90 rescanned longitudinally], 68 recAN, and 207 HC). Next, we applied a "virtual histology" approach to the combined data, investigating relations between interregional profiles of differences in CT and profiles of cell-specific gene expression. Finally, we used the ENIGMA toolbox to relate aforementioned CT profiles to normative structural and functional connectomics.

RESULTS

We confirmed sizeable and widespread reductions of CT as well as volumes (and, to a lesser extent, surface area) in acAN and rapid increases related to partial weight restoration. No differences were detected between either short- or long-term weight-recovered patients and HC. The virtual histology analysis identified associations between gene expression profiles of S1 pyramidal cells and oligodendrocytes and brain regions with more marked differences in CT, whereas the remaining regions were those with a greater expression of genes specific to CA1 pyramidal, astrocytes, microglia, and ependymal cells. Furthermore, the most affected regions were also more functionally and structurally connected.

CONCLUSION

The overall data pattern deviates from findings in other psychiatric disorders. Both virtual histology and connectomics analyses indicated that brain regions most affected in AN are also the most energetically demanding.

Inter- and intra-individual variation in brain structural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.

The association of sleep and cortical thickness in mild cognitive impairment

We investigated whether device-measured sleep parameters are associated with cortical thickness in older adults with probable mild cognitive impairment (MCI). We performed a cross-sectional, exploratory analysis of sleep and structural MRI data. Sleep data were collected with MotionWatch8© actigraphy over 7 days. We computed average and variability for sleep duration, sleep efficiency, and fragmentation index. T1-weighted MRI scans were used to measure cortical thickness in FreeSurfer. We employed surface-based analysis to determine the association between sleep measures and cortical thickness, adjusting for age, sex, Montreal Cognitive Assessment (MoCA) score, and sleep medication use. Our sample included 113 participants (age = 73.1 [5.7], female = 72 [63.7 %]). Higher fragmentation index variability predicted lower cortical thickness in the left superior frontal gyrus (cluster size = 970.9 mm², cluster-wise p = 0.017, cortical thickness range = 2.1 mm² to 3.0 mm²), adjusting for age, sex, MoCA, and sleep medication. Our results suggest that higher variability in sleep fragmentation, an indicator of irregular sleep pattern, is linked to lower cortical thickness. Future longitudinal studies are needed to determine the directionality of these associations.

Neuroanatomical Correlates of Perceived Stress Controllability in Adolescents and Emerging Adults

Stressful life events predict changes in brain structure and increases in psychopathology, but not everyone is equally affected by life stress. The learned helplessness theory posits that perceiving life stressors as uncontrollable leads to depression. Evidence supports this theory for youth, but the impact of perceived control diverges based on stressor type: perceived lack of control over dependent (self-generated) stressors is associated with greater depression symptoms when controlling for the frequency of stress exposure, but perceived control over independent (non-self-generated) stressors is not. However, it is unknown how perceived control over these stressor types is associated with brain structure. We tested whether perceived lack of control over dependent and independent life stressors, controlling for stressor exposure, is associated with gray matter (GM) in a priori regions of interest (ROIs; mPFC, hippocampus, amygdala) and across the cortex in a sample of 108 adolescents and emerging adults ages 14-22. There were no associations across the full sample between perceived control over either stressor type and GM in the ROIs. However, less perceived control over dependent stressors was associated with greater amygdala gray matter volume in female youth and greater medial prefrontal cortex thickness in male youth. Furthermore, whole-cortex analyses revealed less perceived control over dependent stressors was associated with greater GM thickness in cortical regions involved in cognitive and emotional regulation. Thus, appraisals of control have distinct associations with brain morphology while controlling for stressor frequency, highlighting the importance of differentiating between these aspects of the stress experience in future research.

Helmet Technology, Head Impact Exposure, and Cortical Thinning Following a Season of High School Football

The purpose of this study was to compare the effects of wearing older, lower-ranked football helmets (LRank) to wearing newer, higher-ranked football helmets (HRank) on pre- to post-season changes in cortical thickness in response to repetitive head impacts and assess whether changes in cortical thickness are associated with head impact exposure for either helmet type. 105 male high-school athletes (N_HRank = 52, N_LRank = 53) wore accelerometers affixed behind the left mastoid during all practices and games for one regular season of American football to monitor head impact exposure. Pre- and post-season magnetic resonance imaging (MRI) were completed to assess longitudinal changes in cortical thickness. Significant reductions in cortical thickness (i.e., cortical thinning) were observed pre- to post-season for each group, but these longitudinal alterations were not significantly different between the LRank and HRank groups. Further, significant group-by-head impact exposure interactions were observed when predicting changes in cortical thickness. Specifically, a greater frequency of high magnitude head impacts during the football season resulted in greater cortical thinning for the LRank group, but not for the HRank group. These data provide preliminary in vivo evidence that HRank helmets may provide a buffer between the specific effect of high magnitude head impacts on regional thinning by dissipating forces more evenly throughout the cortex. However, future research with larger sample sizes, increased longitudinal measures and additional helmet technologies is warranted to both expand upon and further validate the present study findings.

Association of DNA Methylation of the NLRP3 Gene with Changes in Cortical Thickness in Major Depressive Disorder

The Nod-like receptor pyrin containing 3 (NLRP3) inflammasome has been reported to be a convergent point linking the peripheral immune response induced by psychological stress and neuroinflammatory processes in the brain. We aimed to identify differences in the methylation profiles of the NLRP3 gene between major depressive disorder (MDD) patients and healthy controls (HCs). We also investigated the correlation of the methylation score of loci in NLRP3 with cortical thickness in the MDD group using magnetic resonance imaging (MRI) data. A total of 220 patients with MDD and 82 HCs were included in the study, and genome-wide DNA methylation profiling of the NLRP3 gene was performed. Among the total sample, 88 patients with MDD and 74 HCs underwent T1-weighted structural MRI and were included in the neuroimaging–methylation analysis. We identified five significant differentially methylated positions (DMPs) in NLRP3. In the MDD group, the methylation scores of cg18793688 and cg09418290 showed significant positive or negative correlations with cortical thickness in the occipital, parietal, temporal, and frontal regions, which showed significant differences in cortical thickness between the MDD and HC groups. Our findings suggest that NLRP3 DNA methylation may predispose to depression-related brain structural changes by increasing NLRP3 inflammasome-related neuroinflammatory processes in MDD.

Differences in Cortical Thickness in Schizophrenia Patients With and Without Auditory Verbal Hallucinations

Auditory verbal hallucinations (AVHs) are one of the most common and severe symptoms of schizophrenia (SCZ), but the neuroanatomical mechanisms underlying AVHs remain unclear. This study aimed to investigate whether persistent AVHs (pAVH) are associated with cortical thinning of certain brain regions in patients with SCZ. With the use of the 3T magnetic resonance imaging (MRI) technology, we acquired and analyzed data from 79 SCZ patients with pAVH (pAVH group), 60 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group). The severity of pAVH was assessed by the P3 hallucination items in the Positive and Negative Syndrome Scale (PANSS) and the Auditory Hallucinations Rating Scale (AHRS). Cortical thickness analysis was used to compare the region of interest (ROI) cortical thickness between the groups. The relationship between the severity of pAVH and cortical thickness was also explored. Compared with the non-AVH and HC groups, the pAVH group exhibited significantly reduced cortical thickness in the bilateral lateral orbitofrontal region (p < 0.0007, after Bonferroni correction); no significant difference was found between the non-AVH group and the HC group. The cortical thickness of the left lateral orbitofrontal cortex (P3: r = −0.44, p < 0.001; AHRS: r = −0.45, p < 0.001) and the right lateral orbitofrontal cortex (P3: r = −0.36, p = 0.002; AHRS: r = −0.33, p = 0.004) were negatively correlated with the severity of pAVH (after Bonferroni correction, p < 0.0125). Therefore, abnormal thickness of the bilateral lateral orbitofrontal cortices might be associated with pAVHs in SCZ patients.

The adaptive aging brain

The aging brain is shaped by many structural and functional alterations. Recent cross-disciplinary efforts have uncovered powerful and integrated adaptive mechanisms that promote brain health and prevent functional decline during aging. Here, we review some of the most robust adaptive mechanisms and how they can be engaged to protect, and restore the aging brain.

The ABCD Study: Brain Heterogeneity in Intelligence During a Neurodevelopmental Transition Stage

A complex curvilinear relationship exists between intelligence and age during the neurodevelopment of cortical thickness. To parse out a more fine-grained relationship between intelligence and cortical thickness and surface area, we used a large-scale data set focusing on a critical transition juncture in neurodevelopment in preadolescence. Cortical thickness was derived from T1-weighted structural magnetic resonance images of a large sample of 9- and 11-year-old children from the Adolescent Brain Cognitive Development study. The NIH Toolbox Cognition Battery composite scores, which included fluid, crystallized, and total scores, were used to assess intelligence. Using a double generalized linear model, we assessed the independent association between the mean and dispersion of cortical thickness/surface area and intelligence. Higher intelligence in preadolescents was associated with higher mean cortical thickness in orbitofrontal and primary sensory cortices but with lower thickness in the dorsolateral and medial prefrontal cortex and particularly in the rostral anterior cingulate. The rostral anterior cingulate findings were particularly evident across all subscales of intelligence. Higher intelligence was also associated with greater interindividual similarity in the rostral cingulate. Intelligence during this key transition juncture in preadolescence appears to reflect a dissociation between the cortical development of basic cognitive processes and higher-order executive and motivational processes.

A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.

Gene expression in the dorsolateral and ventromedial prefrontal cortices implicates immune-related gene networks in PTSD

Studies evaluating neuroimaging, genetically predicted gene expression, and pre-clinical genetic models of PTSD, have identified PTSD-related abnormalities in the prefrontal cortex (PFC) of the brain, particularly in dorsolateral and ventromedial PFC (dlPFC and vmPFC). In this study, RNA sequencing was used to examine gene expression in the dlPFC and vmPFC using tissue from the VA National PTSD Brain Bank in donors with histories of PTSD with or without depression (dlPFC n = 38, vmPFC n = 35), depression cases without PTSD (n = 32), and psychopathology-free controls (dlPFC n = 24, vmPFC n = 20). Analyses compared PTSD cases to controls. Follow-up analyses contrasted depression cases to controls. Twenty-one genes were differentially expressed in PTSD after strict multiple testing correction. PTSD-associated genes with roles in learning and memory (FOS, NR4A1), immune regulation (CFH, KPNA1) and myelination (MBP, MOBP, ERMN) were identified. PTSD-associated genes partially overlapped depression-associated genes. Co-expression network analyses identified PTSD-associated networks enriched for immune-related genes across the two brain regions. However, the immune-related genes and association patterns were distinct. The immune gene IL1B was significantly associated with PTSD in candidate-gene analysis and was an upstream regulator of PTSD-associated genes in both regions. There was evidence of replication of dlPFC associations in an independent cohort from a recent study, and a strong correlation between the dlPFC PTSD effect sizes for significant genes in the two studies (r = 0.66, p < 2.2 × 10⁻¹⁶). In conclusion, this study identified several novel PTSD-associated genes and brain region specific PTSD-associated immune-related networks.

The persistent impact of adolescent binge alcohol on adult brain structural, cellular, and behavioral pathology: A role for the neuroimmune system and epigenetics

Adolescence is a critical neurodevelopmental window for maturation of brain structure, neurocircuitry, and glia. This development is sculpted by an individual's unique experiences and genetic background to establish adult level cognitive function and behavioral makeup. Alcohol abuse during adolescence is associated with an increased lifetime risk for developing an alcohol use disorder (AUD). Adolescents participate in heavy, episodic binge drinking that causes persistent changes in neurocircuitry and behavior. These changes may underlie the increased risk for AUD and might also promote cognitive deficits later in life. In this chapter, we have examined research on the persistent effects of adolescent binge-drinking both in humans and in rodent models. These studies implicate roles for neuroimmune signaling as well as epigenetic reprogramming of neurons and glia, which create a vulnerable neuroenvironment. Some of these changes are reversible, giving hope for future treatments to prevent many of the long-term consequences of adolescent alcohol abuse.

Imaging Transcriptomics of Brain Disorders

Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.

Contextualizing adolescent structural brain development: Environmental determinants and mental health outcomes

The spatiotemporal group-level patterns of brain macrostructural development are relatively well-documented. Current research emphasizes individual variability in brain development, including its causes and consequences. Although genetic factors and prenatal and perinatal events play critical roles, calls are now made to also study brain development in transactional interplay with the different aspects of an individual's physical and social environment. Such focus is highly relevant for research on adolescence, a period involving a multitude of contextual changes paralleled by continued refinement of complex cognitive and affective neural systems. Here, we discuss associations between selected aspects of an individual's physical and social environment and adolescent brain structural development and possible links to mental health. We also touch on methodological considerations for future research.

Unveiling the neuroimaging-genetic intersections in the human brain

PURPOSE OF REVIEW

The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data.

RECENT FINDINGS

Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks.

SUMMARY

New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.

Age Influences Loss Aversion Through Effects on Posterior Cingulate Cortical Thickness

Decision-making strategies shift during normal aging and can profoundly affect wellbeing. Although overweighing losses compared to gains, termed "loss aversion," plays an important role in choice selection, the age trajectory of this effect and how it may be influenced by associated changes in brain structure remain unclear. We therefore investigated the relationship between age and loss aversion, and tested for its mediation by cortical thinning in brain regions that are susceptible to age-related declines and are implicated in loss aversion - the insular, orbitofrontal, and anterior and posterior cingulate cortices. Healthy participants (n = 106, 17-54 years) performed the Loss Aversion Task. A subgroup (n = 78) provided structural magnetic resonance imaging scans. Loss aversion followed a curvilinear trajectory, declining in young adulthood and increasing in middle-age, and thinning of the posterior cingulate cortex mediated this trajectory. The findings suggest that beyond a threshold in middle adulthood, atrophy of the posterior cingulate cortex influences loss aversion.

Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition

Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.

New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings

Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.

Cortical Thickness and Its Association with Clinical Cognitive and Neuroimaging Markers in Cerebral Amyloid Angiopathy

BACKGROUND

Cerebral amyloid angiopathy (CAA) contributes to brain neurodegeneration and cognitive decline, but the relationship between these two processes is incompletely understood.

OBJECTIVE

The purpose of this study is to examine cortical thickness and its association with cognition and neurodegenerative biomarkers in CAA.

METHODS

Data were collected from the Functional Assessment of Vascular Reactivity study and the Calgary Normative Study. In total, 48 participants with probable CAA, 72 cognitively normal healthy controls, and 24 participants with mild dementia due to AD were included. Participants underwent an MRI scan, after which global and regional cortical thickness measurements were obtained using FreeSurfer. General linear models, adjusted for age and sex, were used to compare cortical thickness globally and in an AD signature region.

RESULTS

Global cortical thickness was lower in CAA compared to healthy controls (mean difference (MD) -0.047 mm, 95% confidence interval (CI) -0.088, -0.005, p = 0.03), and lower in AD compared to CAA (MD -0.104 mm, 95% CI -0.165, -0.043, p = 0.001). In the AD signature region, cortical thickness was lower in CAA compared to healthy controls (MD -0.07 mm, 95% CI -0.13 to -0.01, p = 0.02). Within the CAA group, lower cortical thickness was associated with lower memory scores (R2 = 0.10; p = 0.05) and higher white matter hyperintensity volume (R2 = 0.09, p = 0.04).

CONCLUSION

CAA contributes to neurodegeneration in the form of lower cortical thickness, and this could contribute to cognitive decline. Regional overlap with an AD cortical atrophy signature region suggests that co-existing AD pathology may contribute to lower cortical thickness observed in CAA.

The trajectory of cortical GABA across the lifespan, an individual participant data meta-analysis of edited MRS studies

γ-Aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the human brain and can be measured with magnetic resonance spectroscopy (MRS). Conflicting accounts report decreases and increases in cortical GABA levels across the lifespan. This incompatibility may be an artifact of the size and age range of the samples utilized in these studies. No single study to date has included the entire lifespan. In this study, eight suitable datasets were integrated to generate a model of the trajectory of frontal GABA estimates (as reported through edited MRS; both expressed as ratios and in institutional units) across the lifespan. Data were fit using both a log-normal curve and a nonparametric spline as regression models using a multi-level Bayesian model utilizing the Stan language. Integrated data show that an asymmetric lifespan trajectory of frontal GABA measures involves an early period of increase, followed by a period of stability during early adulthood, with a gradual decrease during adulthood and aging that is described well by both spline and log-normal models. The information gained will provide a general framework to inform expectations of future studies based on the age of the population being studied.

Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data

Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify functional gene categories that drive these associations, using gene-to-category annotation systems like the Gene Ontology (GO). Here, we show that applying standard GCEA methodology to spatial transcriptomic data is affected by substantial false-positive bias, with GO categories displaying an over 500-fold average inflation of false-positive associations with random neural phenotypes in mouse and human. The estimated false-positive rate of a GO category is associated with its rate of being reported as significantly enriched in the literature, suggesting that published reports are affected by this false-positive bias. We show that within-category gene-gene coexpression and spatial autocorrelation are key drivers of the false-positive bias and introduce flexible ensemble-based null models that can account for these effects, made available as a software toolbox.

Differential Macrophage Responses in Affective Versus Non-Affective First-Episode Psychosis Patients

Increased innate immune activation and inflammation are common findings in psychotic and affective (mood) disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), including increased numbers and activation of monocytes and macrophages. These findings often differ depending on the disorder, for example, we previously found increases in circulating inflammatory cytokines associated with monocytes and macrophages in SCZ, while BD had increases in anti-inflammatory cytokines. Despite these differences, few studies have specifically compared immune dysfunction in affective versus non-affective psychotic disorders and none have compared functional monocyte responses across these disorders. To address this, we recruited 25 first episode psychosis (FEP) patients and 23 healthy controls (HC). FEP patients were further grouped based on the presence (AFF) or absence (NON) of mood disorder. We isolated peripheral blood mononuclear cells and cultured them for 1 week with M-CSF to obtain monocyte-derived macrophages. These cells were then stimulated for 24 h to skew them to inflammatory and alternative phenotypes, in order to identify differences in these responses. Following stimulation with LPS and LPS plus IFNγ, we found that macrophages from the NON-group had diminished inflammatory responses compared to both HC and AFF groups. Interestingly, when skewing macrophages to an alternative phenotype using LPS plus IL-4, the AFF macrophages increased production of inflammatory cytokines. Receiver operating curve analysis showed predictive power of inflammatory cytokine concentrations after LPS stimulation in the AFF group versus NON-group. Our results suggest dysfunctional monocyte responses in both affective and non-affective psychotic disorder, with varying types of immune dysfunction depending on the presence or absence of a mood component.

Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer's disease

Aging and Alzheimer's disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD.

The moderating role of socioeconomic status on level of responsibility, executive functioning, and cortical thinning during adolescence

Brain development is exquisitely sensitive to psychosocial experiences, with implications for neurodevelopmental trajectories, for better or worse. The premise of this investigation was that the level of responsibility in adolescence may relate to brain structure and higher-order cognitive functions. In a sample of 108 adolescents, we focused on cortical thickness (using FreeSurfer) as an indicator of neurodevelopment in regions previously implicated in executive functioning (EF) and examined performance on an EF task outside of the scanner, in the context of level of responsibility. We further investigated whether socioeconomic status (SES) and family stress moderated the relationship between responsibility and brain structure or EF. Findings revealed that greater responsibility was related to thinner left precuneus and right middle frontal cortex. In lower SES adolescents, greater responsibility predicted thinner left precuneus and right middle frontal cortex, which have been consistently implicated in EF. Higher SES adolescents did not show structural differences related to responsibility, however, they did exhibit better EF performance. It may be that circumstances surrounding the need for greater responsibility in lower SES households are detrimental to neurodevelopment compared to higher SES households. Alternatively, responsibility may act as a protective factor that bolsters cortical thinning in regions related to EF.