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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 (βrange = −0.057 to −0.104, all PFDR βrange = 0.071 to 0.115, all PFDR = 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, PFDR = 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.

BackgroundDNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown.ResultsWe analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation.ConclusionsOur results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.

There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including Major Depressive Disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980), and UK Biobank (UKB, N = 8900); for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs, and graph partitioning with Markov Stability to determine optimal clustering of participants. Resultant clusters were i) checked whether they were replicated in an independent cohort, and ii) tested for associations with depression status, and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen's d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case-control status in either cohort (GS subsample: pFDR = 0.2239 - 0.6585; UKB: pFDR = 0.2003 - 0.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets; for CSA, CV, subCV (GS subsample: d = 0.2529 - 0.3490, pFDR < 0.005; UKB: d = 0.0868 - 0.1070, pFDR < 0.005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case-control status.

Highlights • First study of both serum and DNAm CRP associations with depression/neuroimaging. • Serum CRP is associated with somatic symptoms and reduced entorhinal cortex thickness. • DNAm CRP is associated with widespread reductions in white matter integrity. • Evidence for central effects of peripheral inflammation from serum and DNAm markers., Inflammatory processes are implicated in the aetiology of Major Depressive Disorder (MDD); however, the relationship between peripheral inflammation, brain structure and depression remains unclear, partly due to complexities around the use of acute/phasic inflammatory biomarkers. Here, we report the first large-scale study of both serological and methylomic signatures of CRP (considered to represent acute and chronic measures of inflammation respectively) and their associations with depression status/symptoms, and structural neuroimaging phenotypes (T1 and diffusion MRI) in a large community-based sample (Generation Scotland; NMDD cases = 271, Ncontrols = 609). Serum CRP was associated with overall MDD severity, and specifically with current somatic symptoms- general interest (β = 0.145, PFDR = 6 × 10−4) and energy levels (β = 0.101, PFDR = 0.027), along with reduced entorhinal cortex thickness (β = −0.095, PFDR = 0.037). DNAm CRP was significantly associated with reduced global grey matter/cortical volume and widespread reductions in integrity of 16/24 white matter tracts (with greatest regional effects in the external and internal capsules, βFA= −0.12 to −0.14). In general, the methylation-based measures showed stronger associations with imaging metrics than serum-based CRP measures (βaverage = −0.15 versus βaverage = 0.01 respectively). These findings provide evidence for central effects of peripheral inflammation from both serological and epigenetic markers of inflammation, including in brain regions previously implicated in depression. This suggests that these imaging measures may be involved in the relationship between peripheral inflammation and somatic/depressive symptoms. Notably, greater effects on brain morphology were seen for methylation-based rather than serum-based measures of inflammation, indicating the importance of such measures for future studies.

Development of cerebral small vessel disease, a major cause of stroke and dementia, may be influenced by early life factors. It is unclear whether these relationships are independent of each other, of adult socio-economic status or of vascular risk factor exposures. We examined associations between factors from birth (ponderal index, birth weight), childhood (IQ, education, socio-economic status), adult small vessel disease, and brain volumes, using data from four prospective cohort studies: STratifying Resilience And Depression Longitudinally (STRADL) (n = 1080; mean age = 59 years); the Dutch Famine Birth Cohort (n = 118; mean age = 68 years); the Lothian Birth Cohort 1936 (LBC1936; n = 617; mean age = 73 years), and the Simpson’s cohort (n = 110; mean age = 78 years). We analysed each small vessel disease feature individually and summed to give a total small vessel disease score (range 1–4) in each cohort separately, then in meta-analysis, adjusted for vascular risk factors and adult socio-economic status. Higher birth weight was associated with fewer lacunes [odds ratio (OR) per 100 g = 0.93, 95% confidence interval (CI) = 0.88 to 0.99], fewer infarcts (OR = 0.94, 95% CI = 0.89 to 0.99), and fewer perivascular spaces (OR = 0.95, 95% CI = 0.91 to 0.99). Higher childhood IQ was associated with lower white matter hyperintensity burden (OR per IQ point = 0.99, 95% CI 0.98 to 0.998), fewer infarcts (OR = 0.98, 95% CI = 0.97 to 0.998), fewer lacunes (OR = 0.98, 95% CI = 0.97 to 0.999), and lower total small vessel disease burden (OR = 0.98, 95% CI = 0.96 to 0.999). Low education was associated with more microbleeds (OR = 1.90, 95% CI = 1.33 to 2.72) and lower total brain volume (mean difference = −178.86 cm3, 95% CI = −325.07 to −32.66). Low childhood socio-economic status was associated with fewer lacunes (OR = 0.62, 95% CI = 0.40 to 0.95). Early life factors are associated with worse small vessel disease in later life, independent of each other, vascular risk factors and adult socio-economic status. Risk for small vessel disease may originate in early life and provide a mechanistic link between early life factors and risk of stroke and dementia. Policies investing in early child development may improve lifelong brain health and contribute to the prevention of dementia and stroke in older age., Using data from four prospective cohort studies, Backhouse et al. show that early life factors increase the risk of cerebral small vessel disease in later life, independent of each other, vascular risk factors and adult socio-economic status. This may provide a mechanistic link between early life factors and risk of stroke and dementia.

Changes in brain morphology have been reported during development, ageing and in relation to different pathologies. Brain morphology described by the shape complexity of gyri and sulci can be captured and quantified using fractal dimension (FD). This measure of brain structural complexity, as well as brain volume, are associated with intelligence, but less is known about the sexual dimorphism of these relationships. In this paper, sex differences in the relationship between brain structural complexity and general intelligence (g) in two diverse geographic and cultural populations (UK and Indian) are investigated. 3D T1-weighted magnetic resonance imaging (MRI) data and a battery of cognitive tests were acquired from participants belonging to three different cohorts: Mysore Parthenon Cohort (MPC); Aberdeen Children of the 1950s (ACONF) and UK Biobank. We computed MRI derived structural brain complexity and g estimated from a battery of cognitive tests for each group. Brain complexity and volume were both positively corelated with intelligence, with the correlations being significant in women but not always in men. This relationship is seen across populations of differing ages and geographical locations and improves understanding of neurobiological sex-differences.

Background Although treatment-resistant and nontreatment-resistant depressed patients show structural brain anomalies relative to healthy controls, the difference in regional volumetry between these two groups remains undocumented. Methods A whole-brain voxel-based morphometry (VBM) analysis of regional volumes was performed in 125 participants’ magnetic resonance images obtained on a 1.5 Tesla scanner; 41 had treatment-resistant depression (TRD), 40 nontreatment-resistant depression (non-TRD), and 44 were healthy controls. The groups were comparable for age and gender. Bipolar/unipolar features as well as pharmacological treatment classes were taken into account as covariates. Results TRD patients had higher gray matter (GM) volume in the left and right amygdala than non-TRD patients. No difference was found between the TRD bipolar and the TRD unipolar patients, or between the non-TRD bipolar and non-TRD unipolar patients. An exploratory analysis showed that lithium-treated patients in both groups had higher GM volume in the superior and middle frontal gyri in both hemispheres. Conclusions Higher GM volume in amygdala detected in TRD patients might be seen in perspective with vulnerability to chronicity, revealed by medication resistance.

Clinical studies have reported altered reward processing in major depressive disorder. Using dynamic causal modelling, Rupprecher et al. show that blunted reward-related effective connectivity from the medial prefrontal cortex to the striatum is associated with increased severity of depressive symptoms., Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex and basal ganglia has been extensively studied and the former has excitatory glutamatergic projections to the latter. Reduced effect of glutamatergic projections from the prefrontal cortex to the nucleus accumbens has been argued to underlie motivational disorders such as depression, and many prominent theories of major depressive disorder propose a role for abnormal cortico-limbic connectivity. However, it is unclear whether there is abnormal reward-linked effective connectivity between the medial prefrontal cortex and basal ganglia related to depression. While resting state connectivity abnormalities have been frequently reported in depression, it has not been possible to directly link these findings to reward-learning studies. Here, we tested two main hypotheses. First, mood symptoms are associated with blunted striatal reward prediction error signals in a large community-based sample of recovered and currently ill patients, similar to reports from a number of studies. Second, event-related directed medial prefrontal cortex to basal ganglia effective connectivity is abnormally increased or decreased related to the severity of mood symptoms. Using a Research Domain Criteria approach, data were acquired from a large community-based sample of subjects who participated in a probabilistic reward learning task during event-related functional MRI. Computational modelling of behaviour, model-free and model-based functional MRI, and effective connectivity dynamic causal modelling analyses were used to test hypotheses. Increased depressive symptom severity was related to decreased reward signals in areas which included the nucleus accumbens in 475 participants. Decreased reward-related effective connectivity from the medial prefrontal cortex to striatum was associated with increased depressive symptom severity in 165 participants. Decreased striatal activity may have been due to decreased cortical to striatal connectivity consistent with glutamatergic and cortical-limbic related theories of depression and resulted in reduced direct pathway basal ganglia output. Further study of basal ganglia pathophysiology is required to better understand these abnormalities in patients with depressive symptoms and syndromes.

Background: hypertension is a risk for brain ageing, but the mechanisms underlying this effect remain unclear. Magnetic resonance imaging (MRI) detected biomarkers of brain ageing include white matter hyperintensities (WMHs), a marker of cerebrovascular disease, and hippocampal volume, a marker of Alzheimer’s disease pathology. Objective: to examine relationships between blood pressure (BP) components and brain pathology in older adults. Subjects: two hundred and twenty-seven members of the Aberdeen 1936 Birth Cohort between ages 64 and 68 years. Methods: BP was assessed biennially between 64 and 68 years and brain MRI performed at 68 years. The risk factors of interest were diastolic and systolic BP and their visit-to-visit variability. Outcomes were WMH abundance and hippocampal volume. Regression models, controlling for confounding factors, examined their relationships. Results: higher diastolic BP predicted increased WMH (β = 0.13, P = 0.044) and smaller hippocampi (β = −0.25, P = 0.006). In contrast, increased systolic BP predicted larger hippocampi (β = 0.22, P = 0.013). Variability of diastolic BP predicted lower hippocampal volume (β = −0.15, P = 0.033). These relationships were independent of confounding life-course risk factors. Anti-hypertensive medication did not modify these relationships, but was independently associated with increased WMH (β = 0.17, P = 0.011). Conclusion: increased diastolic BP is associated with biomarkers of both cerebrovascular and Alzheimer’s diseases, whereas the role of systolic BP is less clear, with evidence for a protective effect on hippocampal volume. These differing relationships emphasise the importance of considering individual BP components with regard to brain ageing and pathology. Interventions targeting diastolic hypertension and its chronic variability may provide new strategies able to slow the accumulation of these harmful pathologies.

Brain morphology and cognitive ability change with age. Gray and white matter volumes decrease markedly by the 7th decade of life when cognitive decreases first become readily detectable. As a consequence, the shape complexity of the cortical mantle may also change. The purposes of this study are to examine changes over a five year period in brain structural complexity in late life, and to investigate cognitive correlates of any changes. Brain magnetic resonance images at 1.5 Tesla were acquired from the Aberdeen 1936 Birth Cohort at about ages 68 years (243 participants) and 73 years (148 participants returned). Measures of brain complexity were extracted using Fractal Dimension (FD) and calculated using the box-counting method. White matter complexity, brain volumes and cognitive performance were measured at both 68 and 73 years. Childhood ability was measured at age 11 using the Moray House Test. FD and brain volume decrease significantly from age 68 to 73 years. Using a multilevel linear modeling approach, we conclude that individual decreases in late life white matter complexity are not associated with differences in executive function but are linked to information processing speed, auditory-verbal learning, and reasoning in specific models-with adjustment for childhood mental ability. A significant association was found after adjustment for age, brain volume and childhood mental ability. Complexity of white matter is associated with higher fluid cognitive ability and, in a longitudinal study, predicts retention of cognitive ability within late life.

Objective The idea of cortical surface anomalies in subjects with intellectual disability (mental retardation) and schizophrenia can be traced back to early 20th century qualitative observations. Since it is unknown whether modern quantitative measures of cortical complexity and folding would retrieve those early empirical observations, we measured fractal dimension and sulcal span index in photographs of human brains taken in the 1910's. Method Brain photographs were compared between 36 patients with mental retardation and 21 patients with dementia praecox for the fractal dimension and sulcal span index. Also, a mental retardation subgroup with no-or-non-understandable speech (n = 12) was compared with a subgroup with comprehensible speech (n = 23). Results Mental retardation group had a lower whole-brain fractal dimension than dementia praecox, and a higher sulcal span index in left posterior cortex. The mental retardation subgroup with comprehensible speech had a lower fractal dimension in left hemisphere than the subgroup with no-or-non-understandable speech and a lower sulcal index in left posterior cortex. Conclusion Measures of cortical complexity and folding suggest differences between mental retardation and dementia praecox, and regional variations according to language abilities in mental retardation. The findings provide a unique picture of cortical surface changes in their original untreated form, one century ago.

The fractal dimension (FD) was used to reveal brain structure irregularities in patients with schizophrenia. FD provides a unique way of quantifying the shape complexity of cortical folding of the human brain. MR images were obtained from seven patients with schizophrenia that were compared with six healthy control subjects. The MR images were first segmented, and the FD was calculated for the grey/white matter boundary for the whole brain and the hemispheres separately, using the box-counting and Minkowski-Bouligand methods. The results showed that the patients had larger FD values than the controls, for the whole brain volume and right hemisphere.

Background Post-adolescence is known to be a period of general maturation and development in the human brain. In brain imaging, volumetric and morphologic cortical grey-matter changes can easily be assessed, but the analysis of cortical complexity seems to have been broadly neglected for this age interval. Methods Magnetic resonance imaging (MRI) was used to acquire structural brain images. The study involved 17 adolescents (mean age 14.1 ± 0.27, 11 girls) who were compared with 14 young adults (mean age 24.24 ± 2.76, 7 women) for measures of brain complexity (fractal dimension - FD), grey matter (GM) volume and surface-area of cortical ribbon. FD was calculated using box-counting and Minkowski-Bouligand methods; FD and GM volume were measured for the whole brain, each hemisphere and lobes: frontal, occipital, parietal and temporal. Results The results show that the adults have a lower cortical complexity than the adolescents, which was significant for whole brain, left and right hemisphere, frontal and parietal lobes for both genders; and only for males in left temporal lobe. The GM volume was smaller in men than in boys for almost all measurements, and smaller in women than in girls just for right parietal lobe. A significant Pearson correlation was found between FD and GM volume for whole brain and each hemisphere in both genders. The decrease of the GM surface-area was significant in post-adolescence for males, not for females. Conclusions During post-adolescence there are common changes in cortical complexity in the same regions for both genders, but there are also gender specific changes in some cortical areas. The sex differences from different cortical measurements (FD, GM volume and surface-area of cortical ribbon) could suggest a maturation delay in specific brain regions for each gender in relation to the other and might be explained through the functional role of the corresponding regions reflected in gender difference of developed abilities.

MR images were used to look for brain structure irregularities in adolescent children with dyslexia by use of combined grey and white matter volume measurements and fractal dimension (FD) of the grey-white matter border. The data were collected from 13 dyslexic adolescent (8 boys and 5 girls) that were compared with 18 control subjects (8 boys and 10 girls). The MR images were first segmented, and the volume as well as the FD of the grey/white matter border for the whole brain and for each hemisphere was computed. Changes were found in the measured volumes of both grey and white matter and were best reflected in the ratio of grey/white matter and in FD values, especially in the left hemisphere. The results showed that, although dyslexia is less frequent in women, the structural differences in the brain are more pronounced in their case, pointing to an increased vulnerability of the female brain to morphological changes associated with dyslexia.