Multiple markers of cortical morphology reveal evidence of supragranular thinning in schizophrenia.

In vivo structural neuroimaging can reliably identify changes to cortical morphology and its regional variation but cannot yet relate these changes to specific cortical layers. We propose, however, that by synthesizing principles of cortical organization, including relative contributions of different layers to sulcal and gyral thickness, regional patterns of variation in thickness of different layers across the cortical sheet and profiles of layer variation across functional hierarchies, it is possible to develop indirect morphological measures as markers of more specific cytoarchitectural changes. We developed four indirect measures sensitive to changes specifically occurring in supragranular cortical layers, and applied these to test the hypothesis that supragranular layers are disproportionately affected in schizophrenia. Our findings from the four different measures converge to indicate a predominance of supragranular thinning in schizophrenia, independent of medication and illness duration. We propose that these indirect measures offer novel ways of identifying layer-specific cortical changes, offering complementary in vivo observations to existing post-mortem studies.KW is supported by the University of Cambridge MB/PhD Programme and, together with KJW, by the Wellcome Trust. IMG by a Wellcome Trust Strategic Award (RNAG/260), and LR and PCF by the Bernard Wolfe Health Neuroscience Fund and Wellcome Trust

Metabolic flexibility as a major predictor of spatial distribution in microbial communities

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology

Conservative and disruptive modes of adolescent change in human brain functional connectivity

Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: “conservative” and “disruptive.” Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman’s correlation between edgewise baseline FC (at 14 y, FC14) and adolescent change in FC (ΔFC14−26), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas

Cohort profile: The NSPN 2400 Cohort: a developmental sample supporting the Wellcome Trust NeuroScience in Psychiatry Network

Mental and substance use disorders are the leading cause of years lived with disability, worldwide. Other than childhood developmental disorders and neurodegenerative dementias of the elderly, most mental health disorders are first manifest in the second and third decades of life during which the highest proportion of total disability adjusted life years occurs due to their enormous impact on normal, adolescent and young adult functioning; non-syndromal abnormalities can be identified far earlier in life.This study was supported by the Neuroscience in Psychiatry Network, a strategic award from the Wellcome Trust to the University of Cambridge and University College London (095844/Z/11/Z). Additional support was provided by the National Institute for Health (NIHR) Research Cambridge Biomedical Research Centre, the NIHR Collaboration for Leadership in Applied Health Research & Care East of England, and the Medical Research Council (MRC)/Wellcome Trust Behavioural and Clinical Neuroscience Institute

Gene transcription profiles associated with inter-modular hubs and connection distance in human fMRI networks

Graph theoretical methods have been widely used to investigate the topology of large-scale human brain networks constructed from resting state functional magnetic resonance imaging (fMRI). It has been demonstrated that such human functional connectomes have a complex topology comprising integrative components, such as hubs and inter-modular edges, that are associated with proxy markers of greater biological cost. In the absence of secure knowledge of the neurovascular mechanisms linking ensemble oscillations of neuronal populations to low frequency coupling or functional connectivity between regional fMRI time series, it has been challenging to validate fMRI network properties reductionistically. Supportive evidence to date has been mostly provided by analogous results on the relationships between integrative topology and biological cost in other nervous systems. Here, we use microarray data on brain regional expression of 20,737 genes to explore the relationships between fMRI network topology and transcription of genes annotated for biological processes and cellular components. We show that intra-modular degree and inter-modular degree are differently patterned in anatomical space, are differently associated with cytoarchitectonic classes of cortex, and are associated with distinct and statistically independent gene expression profiles. Genes strongly associated with nodes mediating many long-distance and inter-modular connections are significantly enriched for oxidative metabolism and mitochondria as well as for a subset of genes specifically enriched in human supragranular cortical layers. These results are directly supportive of the concept of high cost / high value network hubs in fMRI networks and point to the nascent opportunity to resolve the molecular and cellular substrates of human brain graphs

Body mass index and height over three generations: evidence from the Lifeways cross-generational cohort study

Background: Obesity and its measure of body mass index are strongly determined by parental body size. Debate continues as to whether both parents contribute equally to offspring body mass which is key to understanding the aetiology of the disease. The aim of this study was to use cohort data from three generations of one family to examine the relative maternal and paternal associations with offspring body mass index and how these associations compare with family height to demonstrate evidence of genetic or environmental cross-generational transmission. Methods: 669 of 1082 families were followed up in 2007/8 as part of the Lifeways study, a prospective observational cross-generation linkage cohort. Height and weight were measured in 529 Irish children aged 5 to 7 years and were self-reported by parents and grandparents. All adults provided information on self-rated health, education status, and indicators of income, diet and physical activity. Associations between the weight, height, and body mass index of family members were examined with mixed models and heritability estimates computed using linear regression analysis. Results: Self-rated health was associated with lower BMI for all family members, as was age for children. When these effects were accounted for evidence of familial associations of BMI from one generation to the next was more apparent in the maternal line. Heritability estimates were higher (h2 = 0.40) for mother-offspring pairs compared to father-offspring pairs (h2 = 0.22). In the previous generation, estimates were higher between mothersparents (h2 = 0.54-0.60) but not between fathers-parents (h2 = -0.04-0.17). Correlations between mother and offspring across two generations remained significant when modelled with fixed variables of socioeconomic status, health, and lifestyle. A similar analysis of height showed strong familial associations from maternal and paternal lines across each generation. Conclusions: This is the first family cohort study to report an enduring association between mother and offspring BMI over three generations. The evidence of BMI transmission over three generations through the maternal line in an observational study corroborates the findings of animal studies. A more detailed analysis of geno and phenotypic data over three generations is warranted to understand the nature of this maternal-offspring relationship.TS 24.4.1

Best practices in data analysis and sharing in neuroimaging using MRI

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping, and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world’s neuroimaging data

Physician practices related to use of BMI-for-age and counseling for childhood obesity prevention: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Screening for obesity and providing appropriate obesity-related counseling in the clinical setting are important strategies to prevent and control childhood obesity. The purpose of this study is to document pediatricians (PEDs) and general practitioners (GPs) with pediatric patients use of BMI-for-age to screen for obesity, confidence in explaining BMI, access to referral clinics, and characteristics associated with screening and counseling to children and their caregivers.</p> <p>Methods</p> <p>The authors used 2008 DocStyles survey data to examine these practices at every well child visit for children aged two years and older. Counseling topics included: physical activity, TV viewing time, energy dense foods, fruits and vegetables, and sugar-sweetened beverages. Chi-square tests were used to examine differences in proportions and logistic regression to identify characteristics associated with screening and counseling.</p> <p>Results</p> <p>The final analytic sample included 250 PEDs and 621 GPs. Prevalence of using BMI-for-age to screen for obesity at every well child visit was higher for PEDs than GPs (50% vs. 22%, χ2 = 67.0, p ≤ 0.01); more PEDs reported being very/somewhat confident in explaining BMI (94% vs. GPs, 87%, p < 0.01); more PEDs reported access to a pediatric obesity specialty clinic for referral (PEDs = 65% vs. GPs = 42%, χ2 = 37.5, p ≤ 0.0001).</p> <p>In general, PEDs reported higher counseling prevalence than GPs. There were significant differences in the following topics: TV viewing (PEDs, 79% vs. GPs, 61%, χ2 = 19.1, p ≤ 0.0001); fruit and vegetable consumption (PEDs, 87% vs. GPs, 78%, χ2 = 6.4, p ≤ 0.01). The only characteristics associated with use of BMI for GPs were being female (OR = 2.3, 95% CI = 1.5-3.5) and serving mostly non-white patients (OR = 1.8, 95% CI = 1.1-2.9); there were no significant associations for PEDs.</p> <p>Conclusions</p> <p>The findings for use of BMI-for-age, counseling habits, and access to a pediatric obesity specialty clinic leave room for improvement. More research is needed to better understand why BMI-for-age is not being used to screen at every well child visit, which may increase the likelihood overweight and obese patients receive counseling and referrals for additional services. The authors also suggest more communication between PEDs and GPs through professional organizations to increase awareness of existing resources, and to enhance access and referral to pediatric obesity specialty clinics.</p

Adolescent Tuning of Association Cortex in Human Structural Brain Networks

Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14–24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.This work was supported by the Neuroscience in Psychiatry Network, a strategic award by the Wellcome Trust to the University of Cambridge and University College London (Grant no. 095844/Z/11/Z to E.T.B., I.M.G., P.B.J., P.F., and R.J.D.). Additional support was provided by the National Institute for Health Research Cambridge Biomedical Research Centre and the Medical Research Council (MRC)/Wellcome Trust Behavioural and Clinical Neuroscience Institute. F.V. was supported by the Gates Cambridge Trust. J.S. was supported by the National Institutes of Health (NIH)-Oxford/Cambridge Scholars Program. K.J.W. was supported by a Mozilla Science Lab Fellowship and the Alan Turing Institute under an Engineering and Physical Research Council (EPSRC) grant (EP/N510129/1). P.E.V. was supported by a Medical Research Council (MRC) Bioinformatics Research Fellowship (MR/K020706/1). M.S. was supported by the Winston Churchill Foundation of the United States. A.A.B. was supported by National Institutes of Mental Health (NIMH) Integrated Mentored Patient-Oriented Research Training (IMPORT) in Psychiatry (R25 MH071584)