Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain ...morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (
= 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline
= 3,825, age = 10 ± 1; 2-year follow-up
= 2,081, age = 12 ± 1).
MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed.
In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (
= 0.099-0.281, P
= 0.001-0.043) than MDD-PRS (
= 0.056-0.152, P
= 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (
= 0.084-0.086,
= 1.38 × 10
-4.77 × 10
) but not with any MDD-RVIs (
< 0.05,
> 0.05).
Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.
Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively ...correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or ‘g’)? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate.
There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9–59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1–88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.
Multiple brain imaging studies of negative emotional bias in major depressive disorder (MDD) have used images of fearful facial expressions and focused on the amygdala and the prefrontal cortex. The ...results have, however, been inconsistent, potentially due to small sample sizes (typically N<50). It remains unclear if any alterations are a characteristic of current depression or of past experience of depression, and whether there are MDD-related changes in effective connectivity between the two brain regions.
Activations and effective connectivity between the amygdala and dorsolateral prefrontal cortex (DLPFC) in response to fearful face stimuli were studied in a large population-based sample from Generation Scotland. Participants either had no history of MDD (N=664 in activation analyses, N=474 in connectivity analyses) or had a diagnosis of MDD during their lifetime (LMDD, N=290 in activation analyses, N=214 in connectivity analyses). The within-scanner task involved implicit facial emotion processing of neutral and fearful faces.
Compared to controls, LMDD was associated with increased activations in left amygdala (PFWE=0.031,kE=4) and left DLPFC (PFWE=0.002,kE=33), increased mean bilateral amygdala activation (β=0.0715,P=0.0314), and increased inhibition from left amygdala to left DLPFC, all in response to fearful faces contrasted to baseline. Results did not appear to be attributable to depressive illness severity or antidepressant medication status at scan time.
Most studied participants had past rather than current depression, average severity of ongoing depression symptoms was low, and a substantial proportion of participants were receiving medication. The study was not longitudinal and the participants were only assessed a single time.
LMDD is associated with hyperactivity of the amygdala and DLPFC, and with stronger amygdala to DLPFC inhibitory connectivity, all in response to fearful faces, unrelated to depression severity at scan time. These results help reduce inconsistency in past literature and suggest disruption of ‘bottom-up’ limbic-prefrontal effective connectivity in depression.
•Lifetime MDD is related to higher amygdala and DLPFC activations to fearful faces.•There is increased inhibition from amygdala to DLPFC when viewing fearful faces in LMDD.•Changes are not attributed to acute MDD severity or antidepressant medication status.•Results help substantially reduce ambiguity in the previous depression literature.
Hypothalamic-pituitary-adrenal (HPA) axis dysregulation has been commonly reported in major depressive disorder (MDD), but with considerable heterogeneity of results; potentially due to the ...predominant use of acute measures of an inherently variable/phasic system. Chronic longer-term measures of HPA-axis activity have yet to be systematically examined in MDD, particularly in relation to brain phenotypes, and in the context of early-life/contemporaneous stress. Here, we utilise a temporally stable measure of cumulative HPA-axis function (hair glucocorticoids) to investigate associations between cortisol, cortisone and total glucocorticoids with concurrent measures of (i) lifetime-MDD case/control status and current symptom severity, (ii) early/current-life stress and (iii) structural neuroimaging phenotypes, in N = 993 individuals from Generation Scotland (mean age = 59.1 yrs). Increased levels of hair cortisol were significantly associated with reduced global and lobar brain volumes with reductions in the frontal, temporal and cingulate regions (β
= -0.057 to -0.104, all P
< 0.05). Increased levels of hair cortisone were significantly associated with MDD (lifetime-MDD status, current symptoms, and severity; β
= 0.071 to 0.115, all P
= < 0.05), with early-life adversity (β = 0.083, P = 0.017), and with reduced global and regional brain volumes (global: β = -0.059, P = 0.043; nucleus accumbens: β = -0.075, P
= 0.044). Associations with total glucocorticoids followed a similar pattern to the cortisol findings. In this large community-based sample, elevated glucocorticoids were significantly associated with MDD, with early, but not later-life stress, and with reduced global and regional brain phenotypes. These findings provide important foundations for future mechanistic studies to formally explore causal relationships between early adversity, chronic rather than acute measures of glucocorticoids, and neurobiological associations relevant to the aetiology of MDD.
Purpose
Psychological resilience, the ability to manage and quickly recover from stress and trauma, is associated with a range of health and wellbeing outcomes. Resilience is known to relate to ...personality, self-esteem and positive affect, and may also depend upon childhood experience and stress. In this study, we investigated the role of early-life contributors to resilience and related factors in later life.
Methods
We used data from the 6-day sample of the Scottish mental survey 1947, an initially representative sample of Scottish children born in 1936. They were assessed on a range of factors between the ages of 11 and 27 years, and resilience and other outcomes at 77 years.
Results
Higher adolescent dependability unexpectedly predicted lower resilience in older-age, as did childhood illnesses, while a count of specific stressors experienced throughout early life significantly predicted higher later-life resilience. We also observed significant cross-sectional correlations between resilience and measures of physical health, mental health, wellbeing and loneliness. Some of the associations between early-life predictors and later-life outcomes were significantly mediated by resilience.
Conclusions
Our results support the hypothesis that stress throughout early life may help to build resilience in later-life, and demonstrate the importance of resilience as a mediator of other influences on health and wellbeing in older age. We suggest that the mechanisms determining how early-life stress leads to higher resilience are worthy of further investigation, and that psychological resilience should be a focus of research and a target for therapeutic interventions aiming to improve older-age health and wellbeing.
Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the ...brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region‐to‐region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell‐signalling/modification and transcription factors. We validate these patterns out‐of‐sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta‐analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health‐related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
We validate and characterise two general rules that govern the spatial variation of gene expression across the human cortex and conduct a meta‐analysis of regional cortico‐macrostructural correlates of individual differences in general cognitive functioning (g, N = 39,519). Spatial correlations between cortical profiles of gene expression and g are assessed.
Woody encroachment can lead to a switch from open savannas to dense woodlands or forests. This has implications for both the composition of ecological communities and the provision of ecosystem ...services such as nutrient cycling and grazing capacity. The patterns and underlying drivers responsible for woody encroachment are not fully understood. Here, we investigate the underlying determinants of bush clump formation (a form of encroachment) in a South African savanna and explore whether bush clump succession is driven by deterministic (i.e., predictable changes in species composition) or stochastic (i.e., random) processes. Specifically, we test (1) whether the similarity in species composition of saplings and trees differs among small and large clumps, (2) which environmental factors are driving succession, and (3) whether forest specialization of tree and sapling species within bush clumps increases with the successional gradient. Similarity in species composition between saplings in small clumps and trees in large clumps was higher than similarity between trees in small clumps and trees in large clumps. Furthermore, temperature, soil moisture, relative humidity, and light intensity were related to changes in species composition along the successional gradient. As expected, forest specialization of trees increased with increasing clump area indicating that late‐successional bush clumps have more forest‐type species. The directional changes of species found along the successional gradient suggest a deterministic process of succession driven by changes in local environmental conditions during clump formation.
Woody encroachment, in the form of bush clumps, follows a deterministic process of succession. With succession, these clumps alter the microclimate beneath their canopy creating habitat suitable for the establishment of forest‐type species, leading to the establishment of forest islands scattered throughout the savanna.
Objectives
Current research suggests significant disruptions in functional brain networks in individuals with mood disorder, and in those at familial risk. Studies of structural brain networks ...provide important insights into synchronized maturational change but have received less attention. We aimed to investigate developmental relationships of large‐scale brain networks in mood disorder using structural covariance (SC) analyses.
Methods
We conducted SC analysis of baseline structural imaging data from 121 at the time of scanning unaffected high risk (HR) individuals (29 later developed mood disorder after a median time of 4.95 years), and 89 healthy controls (C‐well) with no familial risk from the Scottish Bipolar Family Study (age 15‐27, 64% female). Voxel‐wise analyses of covariance were conducted to compare the associations between each seed region in visual, auditory, motor, speech, semantic, executive‐control, salience and default‐mode networks and the whole brain signal. SC maps were compared for (a) HR(all) versus C‐well individuals, and (b) between those who remained well (HR‐well), versus those who subsequently developed mood disorder (HR‐MD), and C‐well.
Results
There were no significant differences between HR(all) and C‐well individuals. On splitting the HR group based on subsequent clinical outcome, the HR‐MD group however displayed greater baseline SC in the salience and executive‐control network, and HR‐well individuals showed less SC in the salience network, compared to C‐well, respectively (P < .001).
Conclusions
These findings indicate differences in network‐level inter‐regional relationships, especially within the salience network, which precede onset of mood disorder in those at familial risk.
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