Integrated Visualization of Human Brain Connectome Data

Visualization plays a vital role in the analysis of multi-modal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomic structure. New surface texture techniques are developed to map non-spatial attributes onto the brain surfaces from MRI scans. Two types of non-spatial information are represented: (1) time-series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image based phenotypic biomarkers for brain diseases

Socioeconomic position across the lifecourse & allostatic load: data from the West of Scotland Twenty-07 cohort study

Background: We examined how socioeconomic position (SEP) across the lifecourse (three critical periods, social mobility and accumulated over time) is associated with allostatic load (a measure of cumulative physiological burden). Methods. Data are from the West of Scotland Twenty-07 Study, with respondents aged 35 (n = 740), 55 (n = 817) and 75 (n = 483). SEP measures representing childhood, the transition to adulthood and adulthood SEP were used. Allostatic load was produced by summing nine binary biomarker scores (1 = in the highest-risk quartile). Linear regressions were used for each of the lifecourse models; with model fits compared using partial F-tests. Results: For those aged 35 and 55, higher SEP was associated with lower allostatic load (no association in the 75-year-olds). The accumulation model (more time spent with higher SEP) had the best model fit in those aged 35 (b = -0.50, 95%CI = -0.68, -0.32, P = 0.002) and 55 (b = -0.31, 95%CI = -0.49, -0.12, P < 0.001). However, the relative contributions of each life-stage differed, with adulthood SEP less strongly associated with allostatic load. Conclusions: Long-term, accumulated higher SEP has been shown to be associated with lower allostatic load (less physiological burden). However, the transition to adulthood may represent a particularly sensitive period for SEP to impact on allostatic load. © 2014 Robertson et al.; licensee BioMed Central Ltd

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Adolescent Self-Organization and Adult Smoking and Drinking over Fifty Years of Follow-Up:The British 1946 Birth Cohort

Variations in markers of adolescent self-organization predict a range of economic and health-related outcomes in general population studies. Using a population-based birth cohort study we investigated associations between adolescent self-organization and two common factors over adulthood influencing health, smoking and alcohol consumption. The MRC National Survey of Health and Development (the British 1946 birth cohort) was used to test associations between a dimensional measure of adolescent self-organization derived from teacher ratings, and summary longitudinal measures of smoking and alcohol consumption over the ensuing five decades. Multinomial regression models were adjusted for sex, adolescent emotional and conduct problems, occupational social class of origin, childhood cognition, educational attainment and adult occupational social class. With all covariates adjusted, higher adolescent self-organization was associated with fewer smoking pack years, although not with quitting; there was no association with alcohol consumption across adulthood (none or heavy compared with light to moderate). Adolescent self-organization appears to be protective against smoking, but not against heavy alcohol consumption. Interpretation of this differential effect should be embedded in an understanding of the social and sociodemographic context in which these health behaviours occur over time

Work-family life courses and BMI trajectories in three British birth cohorts.

BACKGROUND/OBJECTIVES: Combining work and family responsibilities has previously been associated with improved health in mid-life, yet little is known about how these associations change over time (both biographical and historical) and whether this extends to body mass index (BMI) trajectories for British men and women. The purpose of this study was to investigate relationships between work-family life courses and BMI trajectories across adulthood (16-42 years) for men and women in three British birth cohorts. SUBJECTS/METHODS: Multiply imputed data from three nationally representative British birth cohorts were used-the MRC National Survey of Health and Development (NSHD; 1946 birth cohort, n=3012), the National Child Development Study (NCDS; 1958 birth cohort, n=9614) and the British Cohort Study (BCS; 1970 birth cohort, n=8140). A typology of work-family life course types was developed using multi-channel sequence analysis, linking annual information on work, partnerships and parenthood from 16 to 42 years. Work-family life courses were related to BMI trajectories using multi-level growth models. Analyses adjusted for indicators of prior health, birthweight, child BMI, educational attainment and socioeconomic position across the life course, and were stratified by gender and cohort. RESULTS: Work-family life courses characterised by earlier transitions to parenthood and weaker long-term links to employment were associated with greater increases in BMI across adulthood. Some of these differences, particularly for work-family groups, which are becoming increasingly non-normative, became more pronounced across cohorts (for example, increases in BMI between 16 and 42 years in long-term homemaking women: NSHD: 4.35 kg m-2, 95% confidence interval (CI): 3.44, 5.26; NCDS: 5.53 kg m-2, 95% CI: 5.18, 5.88; BCS: 6.69 kg m-2, 95% CI: 6.36, 7.02). CONCLUSIONS: Becoming a parent earlier and weaker long-term ties to employment are associated with greater increases in BMI across adulthood in British men and women.Rebecca Lacey, Anne McMunn, Amanda Sacker and Meena Kumari received funding from the European Research Council (grant number: ERC-2011-StG_20101124, PI: Anne McMunn). Steven Bell also received funding from the European Research Council (grant number: ERCStG-2012-309337_Alcohol-Lifecourse, PI: Annie Britton) and UK Medical Research Council/Alcohol Research UK (MR/M006638/1). Amanda Sacker, Anne McMunn and Meena Kumari additionally received support from the Economic and Social Research Council’s International Centre for Life Course Studies in Society and Health (grant number: ES/J019119/1). DK is supported by the UK Medical Research Council (MC_UU_12019/1). The MRC National Survey of Health and Development is funded by the UK Medical Research Council. Peggy McDonough and Diana Worts were supported by the Canadian Institutes of Health Research grant MOP 119526 and the Social Sciences and Humanities Research Council grant 43512-1267

Volunteer Bias in Recruitment, Retention, and Blood Sample Donation in a Randomised Controlled Trial Involving Mothers and Their Children at Six Months and Two Years: A Longitudinal Analysis

BACKGROUND: The vulnerability of clinical trials to volunteer bias is under-reported. Volunteer bias is systematic error due to differences between those who choose to participate in studies and those who do not. METHODS AND RESULTS: This paper extends the applications of the concept of volunteer bias by using data from a trial of probiotic supplementation for childhood atopy in healthy dyads to explore 1) differences between a) trial participants and aggregated data from publicly available databases b) participants and non-participants as the trial progressed 2) impact on trial findings of weighting data according to deprivation (Townsend) fifths in the sample and target populations. 1) a) Recruits (n = 454) were less deprived than the target population, matched for area of residence and delivery dates (n = 6,893) (mean [SD] deprivation scores 0.09[4.21] and 0.79[4.08], t = 3.44, df = 511, p<0.001). b) i) As the trial progressed, representation of the most deprived decreased. These participants and smokers were less likely to be retained at 6 months (n = 430[95%]) (OR 0.29,0.13-0.67 and 0.20,0.09-0.46), and 2 years (n = 380[84%]) (aOR 0.68,0.50-0.93 and 0.55,0.28-1.09), and consent to infant blood sample donation (n = 220[48%]) (aOR 0.72,0.57-0.92 and 0.43,0.22-0.83). ii) Mothers interested in probiotics or research or reporting infants' adverse events or rashes were more likely to attend research clinics and consent to skin-prick testing. Mothers participating to help children were more likely to consent to infant blood sample donation. 2) In one trial outcome, atopic eczema, the intervention had a positive effect only in the over-represented, least deprived group. Here, data weighting attenuated risk reduction from 6.9%(0.9-13.1%) to 4.6%(-1.4-+10.5%), and OR from 0.40(0.18-0.91) to 0.56(0.26-1.21). Other findings were unchanged. CONCLUSIONS: Potential for volunteer bias intensified during the trial, due to non-participation of the most deprived and smokers. However, these were not the only predictors of non-participation. Data weighting quantified volunteer bias and modified one important trial outcome. TRIAL REGISTRATION: This randomised, double blind, parallel group, placebo controlled trial is registered with the International Standard Randomised Controlled Trials Register, Number (ISRCTN) 26287422. Registered title: Probiotics in the prevention of atopy in infants and children

Genome-wide association for major depression through age at onset stratification

BACKGROUND: Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. METHODS: Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer’s disease, and coronary artery disease. RESULTS: We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11–1.21, p = 5.2 × 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. CONCLUSIONS: We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder

Epidemiology and heritability of Major Depressive Disorder, stratified by age of onset, sex, and illness course in Generation Scotland:Scottish Family Health Study (GS:SFHS)

The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found an intriguing difference in heritability between recurrent and single MDD illness course. These findings establish GS:SFHS as a valuable cohort for the genetic investigation of MDD

EGFR interacts with the fusion protein of respiratory syncytial virus strain 2-20 and mediates infection and mucin expression.

Respiratory syncytial virus (RSV) is the major cause of viral lower respiratory tract illness in children. In contrast to the RSV prototypic strain A2, clinical isolate RSV 2-20 induces airway mucin expression in mice, a clinically relevant phenotype dependent on the fusion (F) protein of the RSV strain. Epidermal growth factor receptor (EGFR) plays a role in airway mucin expression in other systems; therefore, we hypothesized that the RSV 2-20 F protein stimulates EGFR signaling. Infection of cells with chimeric strains RSV A2-2-20F and A2-2-20GF or over-expression of 2-20 F protein resulted in greater phosphorylation of EGFR than infection with RSV A2 or over-expression of A2 F, respectively. Chemical inhibition of EGFR signaling or knockdown of EGFR resulted in diminished infectivity of RSV A2-2-20F but not RSV A2. Over-expression of EGFR enhanced the fusion activity of 2-20 F protein in trans. EGFR co-immunoprecipitated most efficiently with RSV F proteins derived from "mucogenic" strains. RSV 2-20 F and EGFR co-localized in H292 cells, and A2-2-20GF-induced MUC5AC expression was ablated by EGFR inhibitors in these cells. Treatment of BALB/c mice with the EGFR inhibitor erlotinib significantly reduced the amount of RSV A2-2-20F-induced airway mucin expression. Our results demonstrate that RSV F interacts with EGFR in a strain-specific manner, EGFR is a co-factor for infection, and EGFR plays a role in RSV-induced mucin expression, suggesting EGFR is a potential target for RSV disease

Human organoid models to study coronavirus infections of the respiratory tract

The coronavirus disease 2019 (COVID-19) pandemic emphasized the need to study coronaviruses more thoroughly. Next to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), humans can be infected by SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), and various seasonal coronaviruses. It is likely that all human coronaviruses have a zoonotic origin and circulated in animal reservoirs before crossing the species barrier into humans. Historically, these viruses have been investigated in vitro and in vivo, mainly utilizing immortalized cell lines and animal models, respectively. Recently, more advanced physiological model systems have been developed to study coronavirus host interactions, with human organoids serving as innovative in vitro tissue culture system that closely mimics human physiology. Organoids provide a promising platform for investigating coronavirus infections, exploring viral tropism, studying host immune responses, and evaluating potential therapeutic interventions. This review explores the origins and use of airway organoids in studying coronaviruses. Additionally, it outlines prospects for leveraging airway organoids for examination of both innate and adaptive immune responses, evaluation of antiviral drugs, and creating intricate co-culture models for enhanced insight into coronavirus infections of the respiratory tract.</p