Uncovering the Genetic Architecture of Major Depression

There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected. We identify four priorities for how the field of MD genetics research may move forward in future years, namely by increasing the sample sizes available for genome-wide association studies (GWASs), greater inclusion of diverse ancestries and low-income countries, the closer integration of psychiatric genetics with electronic medical records, and the development of the neuroscience toolkit for polygenic disorders. A review by McIntosh et al. takes stock of recent rapid progress in the genetics of depression, how it has increased our mechanistic understanding, and how this information could be used to improve patient care in future

Cortical Surface Area Differentiates Familial High Risk Individuals Who Go on to Develop Schizophrenia

BACKGROUND: Schizophrenia is associated with structural brain abnormalities that may be present before disease onset. It remains unclear whether these represent general vulnerability indicators or are associated with the clinical state itself. METHODS: To investigate this, structural brain scans were acquired at two time points (mean scan interval 1.87 years) in a cohort of individuals at high familial risk of schizophrenia (n 5 142) and control subjects (n 5 36). Cortical reconstructions were generated using FreeSurfer. The high-risk cohort was subdivided into individuals that remained well during the study, individuals that had transient psychotic symptoms, and individuals that subsequently became ill. Baseline measures and longitudinal change in global estimates of thickness and surface area and lobar values were compared, focusing on overall differences between high-risk individuals and control subjects and then on group differences within the high-risk cohort. RESULTS: Longitudinally, control subjects showed a significantly greater reduction in cortical surface area compared with the high-risk group. Within the high-risk group, differences in surface area at baseline predicted clinical course, with individuals that subsequently became ill having significantly larger surface area than individuals that remained well during the study. For thickness, longitudinal reductions were most prominent in the frontal, cingulate, and occipital lobes in all high-risk individuals compared with control subjects. CONCLUSIONS: Our results suggest that larger surface areas at baseline may be associated with mechanisms that go above and beyond a general familial disposition. A relative preservation over time of surface area, coupled with a thinning of the cortex compared with control subjects, may serve as vulnerability markers of schizophrenia

Verbal working memory and functional large-scale networks in schizophrenia

The aim of this study was to test whether bilinear and nonlinear effective connectivity (EC) measures of working memory fMRI data can differentiate between patients with schizophrenia (SZ) and healthy controls (HC). We applied bilinear and nonlinear Dynamic Causal Modeling (DCM) for the analysis of verbal working memory in 16 SZ and 21 HC. The connection strengths with nonlinear modulation between the dorsolateral prefrontal cortex (DLPFC) and the ventral tegmental area/substantia nigra (VTA/SN) were evaluated. We used Bayesian Model Selection at the group and family levels to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging was used to assess the connection strengths with nonlinear modulation. The DCM analyses revealed that SZ and HC used different bilinear networks despite comparable behavioral performance. In addition, the connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area showed differences between SZ and HC. The adoption of different functional networks in SZ and HC indicated neurobiological alterations underlying working memory performance, including different connection strengths with nonlinear modulation between the DLPFC and the VTA/SN area. These novel findings may increase our understanding of connectivity in working memory in schizophrenia

Social responsiveness to inanimate entities: Altered white matter in a ‘social synaesthesia’

Judgments about personalities and social traits can be made by relatively brief exposure to animate living things. Here we show that unusual architecture in the microstructure of the human brain is related to atypical mental projections of personality and social structure onto things that are neither living nor animate. Our participants experience automatic, life-long and consistent crossmodal associations between language sequences (e.g., letters, numbers and days) and complex personifications (e.g., A is a businessman; 7 a good-natured woman). Participants with this 'Ordinal Linguistic Personification' (Simner and Hubbard, 2006) which we describe here as a form of social synaesthesia, showed lower fractional anisotropy (FA) values in five clusters at whole-brain significance, compared with non-synaesthetes (in the pre-postcentral gyrus/dorsal corticospinal tract, left superior corona radiata, and the genu, body and left side of the corpus callosum). We found no regions of the brain with increased FA in synaesthetes. A number of these regions with reduced FA play a role in social responsiveness, and our study is the first to show that unusual differences in white matter microstructure in these regions is associated with compelling feelings of social cohesion and personality towards non-animate entities. We show too that altered patterns of connectivity known to typify synaesthesia are not limited to variants involving a 'merging of the senses', but also extend to what might be thought of as a cogno-social variant of synaesthesia, linking language and personality attributes in this surprising way

Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts

BACKGROUND: Neuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined. METHODS: Associations and interactions between neuroticism and general intelligence (g) on MDD, self-reported depression, and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, n=19,200) and UK Biobank (n=90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS. RESULTS: Neuroticism was strongly associated with increased risk for depression and higher psychological distress in both samples. Although intelligence conferred no consistent independent effects on depression, it did increase the risk for depression across samples once neuroticism was adjusted for. Results suggest that higher intelligence may ameliorate the association between neuroticism and self-reported depression although no significant interaction was found for clinical MDD. Intelligence was inversely associated with psychological distress across cohorts. A small interaction was found across samples such that lower psychological distress associates with higher intelligence and lower neuroticism, although effect sizes were small. CONCLUSIONS: From two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on psychological distress. Intelligence does not confer protection against diagnosis of depression in those high in neuroticism

Solar Magnetic Carpet I: Simulation of Synthetic Magnetograms

This paper describes a new 2D model for the photospheric evolution of the magnetic carpet. It is the first in a series of papers working towards constructing a realistic 3D non-potential model for the interaction of small-scale solar magnetic fields. In the model, the basic evolution of the magnetic elements is governed by a supergranular flow profile. In addition, magnetic elements may evolve through the processes of emergence, cancellation, coalescence and fragmentation. Model parameters for the emergence of bipoles are based upon the results of observational studies. Using this model, several simulations are considered, where the range of flux with which bipoles may emerge is varied. In all cases the model quickly reaches a steady state where the rates of emergence and cancellation balance. Analysis of the resulting magnetic field shows that we reproduce observed quantities such as the flux distribution, mean field, cancellation rates, photospheric recycle time and a magnetic network. As expected, the simulation matches observations more closely when a larger, and consequently more realistic, range of emerging flux values is allowed (4e16 - 1e19 Mx). The model best reproduces the current observed properties of the magnetic carpet when we take the minimum absolute flux for emerging bipoles to be 4e16 Mx. In future, this 2D model will be used as an evolving photospheric boundary condition for 3D non-potential modeling.Comment: 33 pages, 16 figures, 5 gif movies included: movies may be viewed at http://www-solar.mcs.st-and.ac.uk/~karen/movies_paper1

Hamiltonian Study of Improved U(1U(1 Lattice Gauge Theory in Three Dimensions

A comprehensive analysis of the Symanzik improved anisotropic three-dimensional U(1) lattice gauge theory in the Hamiltonian limit is made. Monte Carlo techniques are used to obtain numerical results for the static potential, ratio of the renormalized and bare anisotropies, the string tension, lowest glueball masses and the mass ratio. Evidence that rotational symmetry is established more accurately for the Symanzik improved anisotropic action is presented. The discretization errors in the static potential and the renormalization of the bare anisotropy are found to be only a few percent compared to errors of about 20-25% for the unimproved gauge action. Evidence of scaling in the string tension, antisymmetric mass gap and the mass ratio is observed in the weak coupling region and the behaviour is tested against analytic and numerical results obtained in various other Hamiltonian studies of the theory. We find that more accurate determination of the scaling coefficients of the string tension and the antisymmetric mass gap has been achieved, and the agreement with various other Hamiltonian studies of the theory is excellent. The improved action is found to give faster convergence to the continuum limit. Very clear evidence is obtained that in the continuum limit the glueball ratio $M_{S}/M_{A}$ approaches exactly 2, as expected in a theory of free, massive bosons.Comment: 13 pages, 15 figures, submitted to Phys. Rev.