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Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Objective: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. Method: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA–Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. Results: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15–0.97; r range: 0.21–0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. Conclusions: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality.

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.

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.

Background Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

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.

IntroductionChildhood trauma and adversity are common across societies and have strong associations with physical and psychiatric morbidity throughout the life-course. One mechanism through which childhood trauma may predispose individuals to poor psychiatric outcomes, such as raised risk of lifetime depression, could be via associations with brain structure. This study aimed to elucidate the associations between childhood trauma scores and brain structure across two large, independent community cohorts.MethodsThe two samples comprised (i) a subsample of individuals from Generation Scotland with imaging and in-depth phenotyping, including the CTQ-28 (n=1,024); and (ii) individuals from UK Biobank with imaging and a modified summary CTQ measure (n=27,202). This comprised n=28,226 for mega-analysis. Scans were processed using FreeSurfer image processing software, providing cortical and subcortical as well as global brain metrics. Regression models were used to determine associations between these metrics and childhood trauma measures. Associations between childhood trauma measures and psychiatric phenotypes were also explored.ResultsChildhood trauma measures associated with lifetime risk of depression diagnosis with similar ORs across cohorts (OR 1.06, 1.23 GS and UKB respectively), which also related to earlier onset and more recurrent course within both samples. There was also evidence for associations between childhood trauma measures and a range of brain structures. Replicated findings included reduced global brain volumes, reduced cortical surface area but not thickness, with highest effects at mega-analysis seen in the frontal (β=-0.0385, SE=0.0048, p(FDR)=5.43×10−15) and parietal lobes (β=-0.0387, SE=0.005, p(FDR)=1.56×10−14). At a regional level, one subcortical regional volume in particular – the ventral diencephalon (VDc) – displayed significant associations with childhood trauma measures across the two cohorts and at mega-analysis (β=-0.0232, SE=0.0039, p(FDR)=2.91×10−8). There was also evidence for associations with reduced hippocampus, thalamus, and nucleus accumbens volumes, however these were not as consistent across cohorts.DiscussionThere was strong evidence for associations between childhood trauma and reduced global and regional brain volumes across cohorts. In particular, the presence of an association between childhood trauma and the volume of the VDc (which includes the hypothalamic area), with replication, provides further evidence of the importance of neuroendocrine stress response pathways in links between early life stress and clinical outcomes.

BackgroundMajor Depressive Disorder (MDD) is associated with accelerated ageing trajectories including functional markers of ageing, cellular ageing and markers of poor brain health. The biological mechanisms underlying these associations remain poorly understood. Chronic inflammation is also associated with advanced ageing; however, the degree to which long-term inflammation plays a role in ageing in MDD remains unclear, partly due to difficulties differentiating long-term inflammation from acute cross-sectional measures.MethodsHere, we use a longer-term measure of inflammation: a DNA methylation-based marker of C-reactive protein (DNAm CRP), in a large cohort of individuals deeply phenotyped for MDD (Generation Scotland, GS; N=804). We investigate associations between DNAm CRP and serum CRP using linear modelling with two brain ageing neuroimaging-derived phenotypes: (i) a machine learning based measure of brain-predicted age difference (brain-PAD) and (ii) white matter hyperintensities (WMH). We then examine inflammation by depression interaction effects for these brain ageing phenotypes. We sought to replicate findings in an independent sample of older community-dwelling adults (Lothian Birth Cohort 1936, LBC1936; N=615).ResultsDNAm CRP was significantly associated with increased brain-PAD (β=0.111, p=0.015), which was replicated in the independent sample with a similar significant effect size (β=0.114, p=0.012). There were no associations between the inflammation markers and WMH phenotypes in the GS-imaging sample, however in the LBC1936 sample, DNAm CRP was significantly associated with both Wahlund infratentorial (β=0.15, PFDR= 0.006) and Fazekas deep white matter hyperintensity scores (β= 0.116, PFDR=0.033). There were no interaction effects between inflammation and MDD in either cohort.ConclusionsThis study found robust associations between a longer-term marker of inflammation and brain ageing as measured by brain-PAD, consistent across two large independent samples. However, we found no evidence for interaction effects between inflammation and MDD on any brain ageing phenotype in these community-based cohorts. These findings provide evidence that chronic inflammation is associated with increased brain ageing, which is not specific to MDD. Future work should investigate these relationships in clinical samples including with other inflammatory biomarkers and should furthermore aim to determine causal directionality.

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.

Background: Major Depressive Disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.Methods: Participants from Generation Scotland (N=1,109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n=43), MDD-remitted (n=282), or controls (n=784). Analysis included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition (e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)). Results for remitted-MDD were less consistent.Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by g, with no evidence for affective biases in remitted individuals.

ObjectiveA major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behaviour. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia.MethodHere, we examine this issue through two approaches: (i) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments; and (ii) by pooling data (N∼6,000 participants) from cohorts from the ENIGMA-Major Depressive Disorder (ENIGMA-MDD) and ENIGMA-Suicidal Thoughts and Behaviour (ENIGMA-STB) working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behaviour.ResultsOur results suggested a pattern of moderate-to-high correlations between instruments, consistent with the wide range of correlations, r=0.22-0.97, reported in the literature. Two common complex instruments, the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Scale for Suicidal Ideation (SSI), were highly correlated with each other (r=0.83), as were suicidal ideation items from common depression severity questionnaires.ConclusionsOur findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behaviour, but share a core factor with single suicidal ideation items found in depression severity questionnaires. Multi-site collaborations including cohorts that used distinct instruments for suicide risk assessment should be feasible provided that they harmonise across instruments or focus on specific constructs of suicidal thoughts or behaviours.Key pointsQuestion: To inform future suicide research in multi-site international consortia, it is important to examine how different suicide measures relate to each other and whether they can be used interchangeably.Findings: Findings suggest detailed instruments (such as the Columbia Suicide Severity Rating Scale and Beck Scale for Suicidal Ideation) provide valuable information on suicidal thoughts and behaviour, and share a core factor with items on suicidal ideation from depression severity rating scale (such as the Hamilton Depression Rating Scale or the Beck Depression Inventory).Importance: Results from international collaborations can mitigate biases by harmonising distinct suicide risk assessment instruments.Next steps: Pooling data within international suicide research consortia may reveal novel clinical, biological and cognitive correlates of suicidal thoughts and/or behaviour.

DNA methylation is an epigenetic mark associated with gene repression and genome stability. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Rates of aging inferred from these clocks correlate with human health. However, the molecular mechanisms underpinning age-associated DNA methylation changes are unknown. Local DNA sequence plays a strong role in programming DNA methylation levels at individual loci independently of age, but its influence on age-associated DNA methylation changes is unknown. We analysed 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 in the genome. We show that changes in methylation with age are especially apparent at 8,322 low CpG density loci. Using SNP data from the same individuals we demonstrate that DNA methylation trajectories are affected by local sequence polymorphisms at 1,487 loci with low CpG density. More generally, we find that local CpG density is a strong determinant of a CpG’s methylation trajectory and that CpGs located in low CpG density regions are particularly prone to change. Overall, our results 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.

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.

BackgroundInflammatory processes are implicated in the aetiology of Major Depressive Disorder (MDD); however, the relationship between peripheral inflammation, brain structure and depression remains unclear. This study investigates associations between depression, structural neuroimaging measures and two measures of inflammation: serum-based C-reactive protein (CRP) and a methylation-based score for CRP (DNAm CRP) in a large community-based sample.MethodsSerum CRP and DNAm CRP were assessed for participants in Generation Scotland (NMDD cases = 240, Ncontrols = 558) alongside structural brain scans (T1 and diffusion MRI). Linear regression was used to investigate associations between (i) both CRP measures and depressive symptoms, (ii) both CRP measures and structural imaging variables and (iii) inflammation x MDD interaction effects (for both CRP measures) with imaging measures.ResultsIncreased serum CRP was significantly associated with overall MDD symptom severity and specifically with somatic symptoms-general interest (β= 0.145, PFDR = 6×10-4) and energy levels (β= 0.101, PFDR = 0.027) and also reduced entorhinal cortex thickness (β= – 0.095, PFDR = 0.037). DNAm CRP was significantly associated with reduced global grey matter/cortical volume and reduced integrity of 16 white matter tracts and showed larger effect sizes (βaverage = −0.15) compared to serum CRP across all measures (βaverage = 0.01).ConclusionsAcute measures of CRP were related to current depression symptoms, specifically somatic symptoms, whereas methylation signatures of inflammation demonstrated greater differences in global and regional brain structure. This study highlights the utility of combining serological and methylation markers to study chronic inflammation effects on the brain in psychiatric disorders.

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.

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Grant information: STRADL is supported by the Wellcome Trust through a Strategic Award (104036/Z/14/Z). GS:SFHS received core support from the CSO of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). ADM is supported by Innovate UK, the European Commission, the Scottish Funding Council via the Scottish Imaging Network SINAPSE, and the CSO. HCW is supported by a JMAS SIM Fellowship from the Royal College of Physicians of Edinburgh, by an ESAT College Fellowship from the University of Edinburgh, and has received previous funding from the Sackler Trust. LR has previously received financial support from Pfizer (formerly Wyeth) in relation to imaging studies of people with schizophrenia and bipolar disorder. JDH is supported by the MRC. DJM is an NRS Clinician, funded by the CSO. RMR is supported by the British Heart Foundation. ISP-V and MRM are supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health; and MRM is also supported by the MRC (MC_UU_12013/6). JMW is supported by MRC UK Dementia Research Institute and MRC Centre and project grants, EPSRC, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant agreement (666881). DJP is supported by Wellcome Trust Longitudinal Population Study funding (216767/Z/19/Z) the Eva Lester bequest to the University of Edinburgh. AMM is additionally supported by the MRC (MC_PC_17209, MC_PC_MR/R01910X/1, MR/S035818/1), The Wellcome Trust (216767/Z/19/Z ), The Sackler Trust, and has previously received research funding from Pfizer, Eli Lilly, and Janssen. Both AMM and IJD are members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the BBSRC and MRC is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Introduction Various methods are available to measure hippocampal atrophy rate. We compared methods to predict Alzheimer's dementia. Methods Participants with brain imaging at ages 69 and 73 years were identified from a previous study. Simple manual measures and computationally automated volumetry were performed. Receiver operating characteristics assessed the predictive ability of each method at baseline and on logit regression analysis of two serial scans. Results Ten of 149 participants developed Alzheimer's dementia and had lower baseline volumes (3647 vs. 4194 mm3P = .002), rates of volume loss (−126 vs. −36 mm3/y; P = .001), and rates of loss in hippocampal fraction (−8.55 vs. −2.35 x 10−5/y; P = .001). Baseline volume with a rate of change gave the highest area under the curve value of 0.96. Discussion Automated volumetry measuring hippocampal size at age 69 years and subsequent rate of change predicts Alzheimer's dementia development.