Gene-Based Association Tests Using New Polygenic Risk Scores and Incorporating Gene Expression Data

Recently, gene-based association studies have shown that integrating genome-wide association studies (GWAS) with expression quantitative trait locus (eQTL) data can boost statistical power and that the genetic liability of traits can be captured by polygenic risk scores (PRSs). In this paper, we propose a new gene-based statistical method that leverages gene-expression measure-ments and new PRSs to identify genes that are associated with phenotypes of interest. We used a generalized linear model to associate phenotypes with gene expression and PRSs and used a score-test statistic to test the association between phenotypes and genes. Our simulation studies show that the newly developed method has correct type I error rates and can boost statistical power compared with other methods that use either gene expression or PRS in association tests. A real data analysis Figurebased on UK Biobank data for asthma shows that the proposed method is applicable to GWAS

Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer

Unsupervised/self-supervised representation learning in time series is critical since labeled samples are usually scarce in real-world scenarios. Existing approaches mainly leverage the contrastive learning framework, which automatically learns to understand the similar and dissimilar data pairs. Nevertheless, they are restricted to the prior knowledge of constructing pairs, cumbersome sampling policy, and unstable performances when encountering sampling bias. Also, few works have focused on effectively modeling across temporal-spectral relations to extend the capacity of representations. In this paper, we aim at learning representations for time series from a new perspective and propose Cross Reconstruction Transformer (CRT) to solve the aforementioned problems in a unified way. CRT achieves time series representation learning through a cross-domain dropping-reconstruction task. Specifically, we transform time series into the frequency domain and randomly drop certain parts in both time and frequency domains. Dropping can maximally preserve the global context compared to cropping and masking. Then a transformer architecture is utilized to adequately capture the cross-domain correlations between temporal and spectral information through reconstructing data in both domains, which is called Dropped Temporal-Spectral Modeling. To discriminate the representations in global latent space, we propose Instance Discrimination Constraint to reduce the mutual information between different time series and sharpen the decision boundaries. Additionally, we propose a specified curriculum learning strategy to optimize the CRT, which progressively increases the dropping ratio in the training process.Comment: Accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS

Integrating External Controls by Regression Calibration for Genome-Wide Association Study

Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study

Efficient Procedures of Sensitivity Analysis for Structural Vibration Systems with Repeated Frequencies

Derivatives of eigenvectors with respect to structural parameters play an important role in structural design, identification, and optimization. Particularly, calculation of eigenvector sensitivity is considered when the eigenvalues are repeated. A relaxation factor embedded in the combined approximations (CA) method makes it effective to the structural response at various modified designs. The proposed method is feasible after overcoming the defection of irreversibility of the characteristic matrix. Numerical examples show that it is easy to implement the computational procedure, and the method presented in this paper is efficient for the general linear vibration damped systems with repeated frequencies

Association of dietary fat intake with skeletal muscle mass and muscle strength in adults aged 20–59: NHANES 2011–2014

BackgroundSarcopenia, a progressive loss of skeletal muscle mass and strength, needs to initially prevent in the twenties. Meanwhile, there is a lack of research on the effects of fat consumption on skeletal muscle mass and strength in adults aged 20–59. We aimed to assess associations between dietary fat intake and skeletal muscle mass, as measured by appendicular lean mass adjusted for body mass index (ALMBMI), and muscle strength, as represented by handgrip strength adjusted for body mass index (GSMAXBMI), among adults aged 20–59.MethodsDietary fat intake per kilogram of actual body weight was assessed using two 24h recalls, while ALM and GSMAX were measured using DXA and a handgrip dynamometer, respectively. A weighted multiple linear regression model was employed to analyze the association between dietary fat intake and skeletal muscle mass, utilizing data from the National Health and Nutrition Examination Survey spanning from 2011 to 2014. To assess the non-linear relationship and saturation value between dietary fat intake and skeletal muscle mass, a smooth curve fitting approach and a saturation effect analysis model were utilized.ResultsThe study comprised a total of 5356 subjects. After adjusting for confounding factors, there was a positive association observed between dietary fat intake and ALMBMI as well as GSMAXBMI. The relationship between dietary fat intake and ALMBMI showed an inverted U-shaped curve, as did the association with GSMAXBMI. Turning points were observed at 1.88 g/kg/d for total fat intake and ALMBMI, as well as at 1.64 g/kg/d for total fat intake and GSMAXBMI. Furthermore, turning points were still evident when stratifying by gender, age, protein intake, and physical activity. The turning points were lower in individuals with low protein intake(<0.8 g/kg/d) and high levels of physical activity.ConclusionThe moderate dietary fat intake can be beneficial for muscle mass and strength in adults aged 20–59 under specific conditions. Special attention should be directed toward the consumption of fats in individuals with low protein intake and those engaged in high levels of physical activity

Preserving the woody plant tree of life in China under future climate and land-cover changes

The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL both at present and in 2070s. The geographical coverage of TOL branches by current PAs is approx. 9%, and less than 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52-79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high cost for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework, and provides references for decision-makers to preserve the Earth's evolutionary history.Fil: Peng, Shijia. Peking University; ChinaFil: Hu, Ruocheng. Peking University; ChinaFil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Universidade Federal da Integração Latino-Americana; Brasil. University of California; Estados UnidosFil: Luo, Yuan. Peking University; ChinaFil: Lyu, Tong. Peking University; ChinaFil: Zhang, Xiaoling. Peking University; ChinaFil: Zhang, Jian. East China Normal University; ChinaFil: Wang, Zhiheng. Peking University; Chin

Transplantation of Autologous Adipose Stem Cells Lacks Therapeutic Efficacy in the Experimental Autoimmune Encephalomyelitis Model

Multiple sclerosis (MS), characterized by chronic inflammation, demyelination, and axonal damage, is a complicated neurological disease of the human central nervous system. Recent interest in adipose stromal/stem cell (ASCs) for the treatment of CNS diseases has promoted further investigation in order to identify the most suitable ASCs. To investigate whether MS affects the biologic properties of ASCs and whether autologous ASCs from MS-affected sources could serve as an effective source for stem cell therapy, cells were isolated from subcutaneous inguinal fat pads of mice with established experimental autoimmune encephalomyelitis (EAE), a murine model of MS. ASCs from EAE mice and their syngeneic wildtype mice were cultured, expanded, and characterized for their cell morphology, surface antigen expression, osteogenic and adipogenic differentiation, colony forming units, and inflammatory cytokine and chemokine levels in vitro. Furthermore, the therapeutic efficacy of the cells was assessed in vivo by transplantation into EAE mice. The results indicated that the ASCs from EAE mice displayed a normal phenotype, typical MSC surface antigen expression, and in vitro osteogenic and adipogenic differentiation capacity, while their osteogenic differentiation capacity was reduced in comparison with their unafflicted control mice. The ASCs from EAE mice also demonstrated increased expression of pro-inflammatory cytokines and chemokines, specifically an elevation in the expression of monocyte chemoattractant protein-1 and keratin chemoattractant. In vivo, infusion of wild type ASCs significantly ameliorate the disease course, autoimmune mediated demyelination and cell infiltration through the regulation of the inflammatory responses, however, mice treated with autologous ASCs showed no therapeutic improvement on the disease progression

Investigations into the effects of scaffold microstructure on slow-release system with bioactive factors for bone repair

In recent years, bone tissue engineering (BTE) has played an essential role in the repair of bone tissue defects. Although bioactive factors as one component of BTE have great potential to effectively promote cell differentiation and bone regeneration, they are usually not used alone due to their short effective half-lives, high concentrations, etc. The release rate of bioactive factors could be controlled by loading them into scaffolds, and the scaffold microstructure has been shown to significantly influence release rates of bioactive factors. Therefore, this review attempted to investigate how the scaffold microstructure affected the release rate of bioactive factors, in which the variables included pore size, pore shape and porosity. The loading nature and the releasing mechanism of bioactive factors were also summarized. The main conclusions were achieved as follows: i) The pore shapes in the scaffold may have had no apparent effect on the release of bioactive factors but significantly affected mechanical properties of the scaffolds; ii) The pore size of about 400 μm in the scaffold may be more conducive to controlling the release of bioactive factors to promote bone formation; iii) The porosity of scaffolds may be positively correlated with the release rate, and the porosity of 70%–80% may be better to control the release rate. This review indicates that a slow-release system with proper scaffold microstructure control could be a tremendous inspiration for developing new treatment strategies for bone disease. It is anticipated to eventually be developed into clinical applications to tackle treatment-related issues effectively