Recommendations for the use of common outcome measures in pediatric traumatic brain injury research

This article addresses the need for age-relevant outcome measures for traumatic brain injury (TBI) research and summarizes the recommendations by the inter-agency Pediatric TBI Outcomes Workgroup. The Pediatric Workgroup\u27s recommendations address primary clinical research objectives including characterizing course of recovery from TBI, prediction of later outcome, measurement of treatment effects, and comparison of outcomes across studies. Consistent with other Common Data Elements (CDE) Workgroups, the Pediatric TBI Outcomes Workgroup adopted the standard three-tier system in its selection of measures. In the first tier, core measures included valid, robust, and widely applicable outcome measures with proven utility in pediatric TBI from each identified domain including academics, adaptive and daily living skills, family and environment, global outcome, health-related quality of life, infant and toddler measures, language and communication, neuropsychological impairment, physical functioning, psychiatric and psychological functioning, recovery of consciousness, social role participation and social competence, social cognition, and TBI-related symptoms. In the second tier, supplemental measures were recommended for consideration in TBI research focusing on specific topics or populations. In the third tier, emerging measures included important instruments currently under development, in the process of validation, or nearing the point of published findings that have significant potential to be superior to measures in the core and supplemental lists and may eventually replace them as evidence for their utility emerges

Recognition and Degradation of Plant Cell Wall Polysaccharides by Two Human Gut Symbionts

Competition for nutrients contained in diverse types of plant cell wall-associated polysaccharides may explain the evolution of substrate-specific catabolic gene modules in common bacterial members of the human gut microbiota

Young Adults’ Conceptions of the Sacred in Finland Today

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Computational Study of the Human Dystrophin Repeats: Interaction Properties and Molecular Dynamics

Dystrophin is a large protein involved in the rare genetic disease Duchenne muscular dystrophy (DMD). It functions as a mechanical linker between the cytoskeleton and the sarcolemma, and is able to resist shear stresses during muscle activity. In all, 75% of the dystrophin molecule consists of a large central rod domain made up of 24 repeat units that share high structural homology with spectrin-like repeats. However, in the absence of any high-resolution structure of these repeats, the molecular basis of dystrophin central domain's functions has not yet been deciphered. In this context, we have performed a computational study of the whole dystrophin central rod domain based on the rational homology modeling of successive and overlapping tandem repeats and the analysis of their surface properties. Each tandem repeat has very specific surface properties that make it unique. However, the repeats share enough electrostatic-surface similarities to be grouped into four separate clusters. Molecular dynamics simulations of four representative tandem repeats reveal specific flexibility or bending properties depending on the repeat sequence. We thus suggest that the dystrophin central rod domain is constituted of seven biologically relevant sub-domains. Our results provide evidence for the role of the dystrophin central rod domain as a scaffold platform with a wide range of surface features and biophysical properties allowing it to interact with its various known partners such as proteins and membrane lipids. This new integrative view is strongly supported by the previous experimental works that investigated the isolated domains and the observed heterogeneity of the severity of dystrophin related pathologies, especially Becker muscular dystrophy

The Human Proteins MBD5 and MBD6 Associate with Heterochromatin but They Do Not Bind Methylated DNA

BACKGROUND: MBD5 and MBD6 are two uncharacterized mammalian proteins that contain a putative Methyl-Binding Domain (MBD). In the proteins MBD1, MBD2, MBD4, and MeCP2, this domain allows the specific recognition of DNA containing methylated cytosine; as a consequence, the proteins serve as interpreters of DNA methylation, an essential epigenetic mark. It is unknown whether MBD5 or MBD6 also bind methylated DNA; this question has interest for basic research, but also practical consequences for human health, as MBD5 deletions are the likely cause of certain cases of mental retardation. PRINCIPAL FINDINGS: Here we report the first functional characterization of MBD5 and MBD6. We have observed that the proteins colocalize with heterochromatin in cultured cells, and that this localization requires the integrity of their MBD. However, heterochromatic localization is maintained in cells with severely decreased levels of DNA methylation. In vitro, neither MBD5 nor MBD6 binds any of the methylated sequences DNA that were tested. CONCLUSIONS: Our data suggest that MBD5 and MBD6 are unlikely to be methyl-binding proteins, yet they may contribute to the formation or function of heterochromatin. One isoform of MBD5 is highly expressed in oocytes, which suggests a possible role in epigenetic reprogramming after fertilization

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

A genome-wide association study of anorexia nervosa

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10−7) in SOX2OT and rs17030795 (P=5.84×10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10−6) between CUL3 and FAM124B and rs1886797 (P=8.05×10−6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4×10−6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field

Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies

Background: The 2016 Dar Es Salaam Call to Action on Diabetes and Other non-communicable diseases (NCDs) advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends from 1980 to 2014 in age-standardized mean body mass index (BMI) and diabetes prevalence in these countries, in order to assess the co-progression and assist policy formulation. Methods: We pooled data from African and worldwide population-based studies which measured height, weight and biomarkers to assess diabetes status in adults aged ≥ 18 years. A Bayesian hierarchical model was used to estimate trends by sex for 200 countries and territories including 53 countries across five African regions (central, eastern, northern, southern and western), in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of ≥ 7.0 mmol/l, history of diabetes diagnosis, or use of insulin or oral glucose control agents). Results: African data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n = 17), Nigeria (n = 15) and Egypt (n = 13); and for diabetes estimates, Tanzania (n = 8), Tunisia (n = 7), and Cameroon, Egypt and South Africa (all n = 6). The age-standardized mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3–21.7) to 23.0 kg/m2 (22.7–23.3) in men, and from 21.9 kg/m2 (21.3–22.5) to 24.9 kg/m2 (24.6–25.1) in women. The age-standardized prevalence of diabetes increased from 3.4% (1.5–6.3) to 8.5% (6.5–10.8) in men, and from 4.1% (2.0–7.5) to 8.9% (6.9–11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃ 0.9) was observed between mean BMI and diabetes prevalence in both sexes in 1980 and 2014. Conclusions: These estimates, based on limited data sources, confirm the rapidly increasing burden of diabetes in Africa. This rise is being driven, at least in part, by increasing adiposity, with regional variations in observed trends. African countries’ efforts to prevent and control diabetes and obesity should integrate the setting up of reliable monitoring systems, consistent with the World Health Organization’s Global Monitoring System Framework

Common Genetic Variation And Age at Onset Of Anorexia Nervosa

Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe