Project description:MotivationPolygenic scores have become a central tool in human genetics research. LDpred is a popular method for deriving polygenic scores based on summary statistics and a matrix of correlation between genetic variants. However, LDpred has limitations that may reduce its predictive performance.ResultsHere, we present LDpred2, a new version of LDpred that addresses these issues. We also provide two new options in LDpred2: a 'sparse' option that can learn effects that are exactly 0, and an 'auto' option that directly learns the two LDpred parameters from data. We benchmark predictive performance of LDpred2 against the previous version on simulated and real data, demonstrating substantial improvements in robustness and predictive accuracy compared to LDpred1. We then show that LDpred2 also outperforms other polygenic score methods recently developed, with a mean AUC over the 8 real traits analyzed here of 65.1%, compared to 63.8% for lassosum, 62.9% for PRS-CS and 61.5% for SBayesR. Note that LDpred2 provides more accurate polygenic scores when run genome-wide, instead of per chromosome.Availability and implementationLDpred2 is implemented in R package bigsnpr.Supplementary informationSupplementary data are available at Bioinformatics online.
Project description:Our autobiographical self depends on the differential recollection of our personal past, notably including memories of morally laden events. Whereas both emotion and temporal recency are well known to influence memory, very little is known about how we remember moral events, and in particular about the distribution in time of memories for events that were blameworthy or praiseworthy. To investigate this issue in detail, we collected a novel database of 758 confidential, autobiographical narratives for personal moral events from 100 well-characterized healthy adults. Negatively valenced moral memories were significantly more remote than positively valenced memories, both as measured by the valence of the cue word that evoked the memory as well as by the content of the memory itself. The effect was independent of chronological age, ethnicity, gender or personality, arguing for a general emotional bias in how we construct our moral autobiography.
Project description:The human microbiome has emerged as the crucial moderator in the interactions between food and our body. It is increasingly recognised that the microbiome can change our mind and health status, or switch on a wide range of diseases including cancer, cardio-metabolic diseases, allergies, and obesity. The causes of diseases are often only partially understood. However, nutrients, metabolites, and microbes are increasingly regarded as key players, even where the complete disease mechanisms remain unclear. The key to progress in the future will be to use and exploit additional, newly emerging disciplines such as metagenomics to complement patient information and to bring our understanding of diseases and the interrelation and effects of nutritional molecules to the next level. The EU has already funded 216 projects under the 7th Framework Programme and Horizon 2020 programmes to promote metagenomics and to advance our knowledge of microbes. This support started with the catalysing MetaHIT project that has produced a catalogue of gut microbes, and has arrived now at the very multi-disciplinary SYSCID action looking at how the microbiome is driving its resilience potential and our health. Together, these projects involve an investment of more than €498 M. However, in Horizon 2020, the new EU Health and Food Work Programmes for 2018-2020 go even further by setting new goals to find applications and to generate more knowledge on the microbiome, nutrition, various hosts of microbes, and their relation to health and disease. The big vision is to modulate health and diseases via the microbiome and nutrition, while at the same time other factors such as omics, molecular signatures, and lifestyle are constant. In this way, microbiome and nutrition research is moving from an isolated and despised offside position to a beacon of hope with a lot of potential and possibilities.
Project description:While mothering is often instinctive and stereotyped in species-specific ways, evolution can favor genetically "open" behavior programs that allow experience to shape infant care. Among experience-dependent maternal behavioral mechanisms, sensory learning about infants has been hard to separate from motivational changes arising from sensitization with infants. We developed a paradigm in which sensory learning of an infant-associated cue improves a stereotypical maternal behavior in female mice. Mice instinctively employed a spatial memory-based strategy when engaged repetitively in a pup search and retrieval task. However, by playing a sound from a T-maze arm to signal where a pup will be delivered for retrieval, mice learned within 7?days and retained for at least 2?weeks the ability to use this specific cue to guide a more efficient search strategy. The motivation to retrieve pups also increased with learning on average, but their correlation did not explain performance at the trial level. Bilaterally silencing auditory cortical activity significantly impaired the utilization of new strategy without changing the motivation to retrieve pups. Finally, motherhood as compared to infant-care experience alone accelerated how quickly the new sensory-based strategy was acquired, suggesting a role for the maternal hormonal state. By rigorously establishing that newly formed sensory associations can improve the performance of a natural maternal behavior, this work facilitates future studies into the neurochemical and circuit mechanisms that mediate novel sensory learning in the maternal context, as well as more learning-based mechanisms of parental behavior in rodents.
Project description:PHASTER (PHAge Search Tool - Enhanced Release) is a significant upgrade to the popular PHAST web server for the rapid identification and annotation of prophage sequences within bacterial genomes and plasmids. Although the steps in the phage identification pipeline in PHASTER remain largely the same as in the original PHAST, numerous software improvements and significant hardware enhancements have now made PHASTER faster, more efficient, more visually appealing and much more user friendly. In particular, PHASTER is now 4.3× faster than PHAST when analyzing a typical bacterial genome. More specifically, software optimizations have made the backend of PHASTER 2.7X faster than PHAST, while the addition of 80 CPUs to the PHASTER compute cluster are responsible for the remaining speed-up. PHASTER can now process a typical bacterial genome in 3 min from the raw sequence alone, or in 1.5 min when given a pre-annotated GenBank file. A number of other optimizations have also been implemented, including automated algorithms to reduce the size and redundancy of PHASTER's databases, improvements in handling multiple (metagenomic) queries and higher user traffic, along with the ability to perform automated look-ups against 14 000 previously PHAST/PHASTER annotated bacterial genomes (which can lead to complete phage annotations in seconds as opposed to minutes). PHASTER's web interface has also been entirely rewritten. A new graphical genome browser has been added, gene/genome visualization tools have been improved, and the graphical interface is now more modern, robust and user-friendly. PHASTER is available online at www.phaster.ca.
Project description:BackgroundCoronary microvascular dysfunction (CMD) is usually evaluated measuring coronary flow velocity reserve (CFVR). A more comprehensive analysis of CFVR including additional consideration of the associated logical companion-CFVR, where hyperemic diastolic coronary flow velocity may act as surrogate, was applied in this study to elucidate the mechanism of CMD in psoriasis.Methods and resultsCoronary flow velocity reserve was analysed using transthoracic echocardiographs of 127 psoriasis patients (age 36 ± 8 years; 104 males) and of 52 sex- and age-matched healthy controls. CFVR determination was repeated in the patient subgroup (n = 78) receiving anti-inflammatory therapy. Baseline and hyperemic microvascular resistance (MR) were calculated. CMD was defined as CFVR ≤ 2.5. Four endotypes of CMD were identified referring to concordant or discordant impairments of hyperemic flow or CFVR. We evaluated the companion-CFVR, as derived from the quadratic mean of hyperemic and diastolic flow velocity at rest. Coronary flow parameters, including CFVR (p = 0.01), were different among the two endotypes having CFVR > 2.5. Specifically, all 11 (14%) patients with CFVR deterioration despite therapy, belonged to endotype 1, and had higher baseline and hyperemic MR (p < 0.0001, both). Interestingly, while CFVR was comparable in patients with worsened versus those with improved CFVR, the companion-CFVR could discriminate by being lower in patients with worsened CFVR (p = 0.01).ConclusionsThe reduced CFVR in psoriasis is driven by decreased companion-CFVR, combined with increased hyperemic MR. Adoption of the mandatory companion-CFVR enables a personalized characterization superior to that achieved by exclusive consideration of CFVR.
Project description:CLARITY is a hydrogel embedding clearing method that has the advantages of transparency, different tissue compatibility and immunostaining compatibility. However, there are also some limitations to CLARITY as it requires a long time to achieve transparency, and the electrophoresis clearing is complex. Therefore, we aimed to simplify the electrophoresis system and shorten the processing time of CLARITY. In our study, we developed a non-circulation electrophoresis system to achieve easier manipulation of electrophoresis clearing. We modified the original CLARITY protocol in hydrogel embedding methods, clearing buffer and immunostaining. When comparing brains processed by our modified method or the original protocol, we found our modifications permit faster and more efficient clearing and labeling. Moreover, we developed a new clearing method named Passive pRe-Electrophroresis CLARITY (PRE-CLARITY) and a new immunostaining method named Centrifugation-Expansion staining (CEx staining). PRE-CLARITY achieved faster clearing and higher transparency, and CEx staining accomplished intact mouse brain labeling faster. With our modifications to CLARITY, we accomplished intact mouse brain clearing and immunostaining within one week, while this requires weeks to months with the original CLARITY. Our studies would allow high-content tracing and analysis of intact brain or other large-scale samples in a short time.