Thomas Nickson

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen’s d effect sizes: −0.10 to −0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: −0.26 to −0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

Subcortical volumetric abnormalities in bipolar disorder.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case–control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen’s d=−0.232; P=3.50 × 10−7) and thalamus (d=−0.148; P=4.27 × 10−3) and enlarged lateral ventricles (d=−0.260; P=3.93 × 10−5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.

White matter integrity and its association with affective and interpersonal symptoms in borderline personality disorder

Background Borderline personality disorder (BPD) is a severe psychiatric disorder involving a range of symptoms including marked affective instability and disturbances in interpersonal interactions. Neuroimaging studies are beginning to provide evidence of altered processing in fronto-limbic network deficits in the disorder, however, few studies directly examine structural connections within this circuitry together with their relation to proposed causative processes and clinical features. Methods In the current study, we investigated whether individuals with BPD (n = 20) have deficits in white matter integrity compared to a matched group of healthy controls (n = 18) using diffusion tensor MRI (DTI). We hypothesized that the BPD group would have decreased fractional anisotropy (FA), a measure of white matter integrity, compared to the controls in white matter tracts connecting frontal and limbic regions, primarily the cingulum, fornix and uncinate fasciculus. We also investigated the extent to which any such deficits related to childhood adversity, as measured by the childhood trauma questionnaire, and symptom severity as measured by the Zanarini rating scale for BPD. Results We report decreased white matter integrity in BPD versus controls in the cingulum and fornix. There were no significant relationships between FA and measures of childhood trauma. There were, however, significant associations between FA in the cingulum and clinical symptoms of anger, and in the fornix with affective instability, and measures of avoidance of abandonment from the Zanarini rating scale. Conclusions We report deficits within fronto-limbic connections in individuals with BPD. Abnormalities within the fornix and cingulum were related to severity of symptoms and highlight the importance of these tracts in the pathogenesis of the disorder.

Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium

BACKGROUND Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. METHODS This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores). RESULTS Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged. CONCLUSIONS Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Longitudinal differences in white matter integrity in youth at high familial risk for bipolar disorder

Previous neuroimaging studies have reported abnormalities in white matter (WM) pathways in subjects at high familial risk of mood disorders. In the current study, we examined the trajectory of these abnormalities during the early stages of illness development using longitudinal diffusion tensor imaging (DTI) data.

Geometric computations by broadcasting automata

In this paper we introduce and apply a novel approach for self-organisation, partitioning and pattern formation on the non-oriented grid environment. The method is based on the generation of nodal patterns in the environment via sequences of discrete waves. The power of the primitives is illustrated by giving solutions to two geometric problems using the broadcast automata model arranged in an integer grid (a square lattice) formation. In this model automata cannot directly observe their neighbours’ state and can only communicate with neighbouring automata through the non-oriented broadcast of messages from a finite alphabet. In particular we show linear time algorithms for the problem of finding the centre of a digital disk starting from any point on the border of the disc and the problem of electing a set of automata that form the inscribed square of such a digital disk. Possible generalizations and applications of techniques based on nodal patterns and the construction of different discrete wave interference pictures are discussed in the conclusion.

Geometric computations by broadcasting automata on the integer grid

In this paper we introduce and apply a novel approach for self-organiz- ation, partitioning and pattern formation on the nonoriented grid environment. The method is based on the generation of nodal patterns in the environment via sequences of discrete waves. The power of the primitives is illustrated by giving solutions to two geometric problems using the broadcast automata model arranged in an integer grid (a square lattice) formation. In particular we show linear time algorithms for: the problem of finding the centre of a digital disk starting from any point on the border of the disc and the problem of electing a set of automata that form the inscribed square of such a digital disk.

White matter differences in major depression: meta-analytic findings from enigma-MDD DTI

Background and Aims: Depression and anxiety are risk factors for developing Coronary heart Disease (CHD), and are associated with poor disease outcomes and mortality. However, there is little information describing repeated measures and longitudinal data that may study the trajectories of depression and anxiety over time,how these are manifested in the context of CHD, and their relationship to sociodemographic measures, cardiac risk factors, and measures of disability. Methods: Using a primary care cohort of 803 patients with a diagnosis of CHD, a latent class growth curve model was developed to study the distinct trajectories of depression and anxiety symptoms over a 3 year period, with 7 distinct 6-month follow-up points.Logistic regression analysis was then conducted to study the association between latent classes and baseline risk factors. Results: The 5-class model yielded the best combination of statistical best-fit analysis and clinical correlation. These classes were:‘stable asymptomatic’ (n = 558), ‘increasing symptoms’ (n = 64),‘decreasing symptoms’ (n = 15), ‘chronic highly symptomatic’(n = 55), and ‘fluctuating symptoms’ (n = 111).The comparison group was the ‘stable asymptomatic’ class. Female sex was associated with the ‘fluctuating class’. Non-white ethnicity was associated with ‘chronic high’ and ‘worsening’ class. Current smoking was associated with all classes, particularly the ‘chronic high’ class.Chest pain was associated strongly with ‘chronic high’ class. Multi-variate models will analyse these associations further. Conclusions: The distinct trajectories of depression and anxiety in CHD will provide important information on the specific ways in which these symptoms affect patients, and provide unique insight into the monitoring and management of this comorbidity.

Discrete discs and broadcasting sequences

Neighbourhood Sequences are deemed to be important in many practical applications within digital imaging through their application in measuring digital distance. Aggregation of neighbourhood sequences based on classical digital distance functions was proposed as an alternative method for organising swarms or robots on the non-oriented grid environment in [1]. Wave phenomena generated nodal patterns in a discrete environment via the two neighbourhood sequences providing a distributed algorithm to find the centre of a digital disc. The geometric shapes that can be formed by such sequences in 2-D are quite limited and so constraints are relaxed to allow any two points at euclidean distance r (r-neighbours) such neighbourhoods represented by the digital disc of radius r.