Burning in the growing season

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Global epigenomic reconfiguration during mammalian brain development

DNA methylation is implicated in mammalian brain development and plasticity underlying learning and memory. We report the genome-wide composition, patterning, cell specificity, and dynamics of DNA methylation at single-base resolution in human and mouse frontal cortex throughout their lifespan. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis. During this period, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. Moreover, we found an mCH signature that identifies genes escaping X-chromosome inactivation. Last, whole-genome single-base resolution 5-hydroxymethylcytosine (hmC) maps revealed that hmC marks fetal brain cell genomes at putative regulatory regions that are CG-demethylated and activated in the adult brain and that CG demethylation at these hmC-poised loci depends on Tet2 activity

Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame

Participating in competitive races can be a thrilling experience for athletes, involving a rush of excitement and sensations of flow, achievement, and self-fulfilment. However, for non-athletes, the prospect of competition is often a scary one which affects intrinsic motivation negatively, especially for less fit, less competitive individuals. We propose a novel method making the positive racing experience accessible to non-athletes using a high-intensity cycling VR exergame: by recording and replaying all their previous gameplay sessions simultaneously, including a projected future performance, players can race against a crowd of "ghost" avatars representing their individual fitness journey. The experience stays relevant and exciting as every race adds a new competitor. A longitudinal study over four weeks and a cross-sectional study found that the new method improves physical performance, intrinsic motivation, and flow compared to a non-competitive exergame. Additionally, the longitudinal study provides insights into the longer-term effects of VR exergames

MicroRNAs Classify Different Disease Behavior Phenotypes of Crohnʼs Disease and May Have Prognostic Utility:

Article first published online 6 July 2015.Supplemental Digital Content is Available in the Text.Background:There is a dire need for reliable prognostic markers that can guide effective therapeutic intervention in Crohn's disease (CD). We examined whether different phenotypes in CD can be classified based on colonic microRNA (miRNA) expression and whether miRNAs have prognostic utility for CD.Methods:High-throughput sequencing of small and total RNA isolated from colon tissue from patients with CD and controls without Inflammatory Bowel Disease (non-IBD) was performed. To identify miRNAs associated with specific phenotypes of CD, patients were stratified according to disease behavior (nonstricturing, nonpenetrating; stricturing; penetrating), and miRNA profiles in each subset were compared with those of the non-IBD group. Validation assays were performed using quantitative reverse transcription polymerase chain reaction. These miRNAs were further evaluated by quantitative reverse transcriptase polymerase chain reaction on formalin-fixed, paraffin-embedded tissue (index biopsies) of patients with nonpenetrating CD at the time of diagnosis that either retained the nonpenetrating phenotype or progressed to penetrating/fistulizing CD.Results:We found a suite of miRNAs, including miR-31-5p, miR-215, miR-223-3p, miR-196b-5p, and miR-203 that stratify patients with CD according to disease behavior independent of the effect of inflammation. Furthermore, we also demonstrated that expression levels of miR-215 in index biopsies of patients with CD might predict the likelihood of progression to penetrating/fistulizing CD. Finally, using a novel statistical simulation approach applied to colonic RNA-sequencing data for patients with CD and non-IBD controls, we identified miR-31-5p and miR-203 as candidate master regulators of gene expression profiles associated with CD.Conclusions:miRNAs may serve as clinically useful prognostic markers guiding initial therapy and identifying patients who would benefit most from effective intervention

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10−8), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P <5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.Peer reviewe