Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and ...osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and genomics'. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.
Background
Increasing evidence suggests that human gut microbiome plays an important role in variation of skeletal muscle mass (SMM). However, specific causal mechanistic relationship of human gut ...microbiome with SMM remains largely unresolved. Understanding the causal mechanistic relationship may provide a basis for novel interventions for loss of SMM. This study investigated whether human gut microbiome has a causal effect on SMM among Chinese community‐dwelling healthy menopausal women.
Methods
Estimated SMM was derived from whole‐body dual‐energy X‐ray absorptiometry. We performed integrated analyses on whole‐genome sequencing, shotgun metagenomic sequencing, and serum short‐chain fatty acids (SCFAs), as well as available host SMM measurements among community‐dwelling healthy menopausal women (N = 482). We combined the results with summary statistics from genome‐wide association analyses for human gut microbiome (N = 952) and SMM traits (N = 28 330). As a prerequisite for causality, we used a computational protocol that was proposed to measure correlations among gut metagenome, metabolome, and the host trait to investigate the relationship between human gut microbiome and SMM. Causal inference methods were applied to assess the potential causal effects of gut microbial features on SMM, through one‐sample and two‐sample Mendelian randomization (MR) analyses, respectively.
Results
In metagenomic association analyses, the increased capacity for gut microbial synthesis of the SCFA butyrate was significantly associated with serum butyrate levels Spearman correlation coefficient (SCC) = 0.13, P = 0.02 and skeletal muscle index (SCC = 0.084, P = 0.002). Of interest was the finding that two main butyrate‐producing bacterial species were both positively associated with the increased capacity for gut microbial synthesis of butyrate Faecalibacterium prausnitzii (SCC = 0.25, P = 6.6 × 10−7) and Butyricimonas virosa (SCC = 0.15, P = 0.001) and for skeletal muscle index F. prausnitzii (SCC = 0.16, P = 6.2 × 10−4) and B. virosa (SCC = 0.17, P = 2.4 × 10−4). One‐sample MR results showed a causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.04, 95% confidence interval 0.029 to 0.051, P = 0.003). Two‐sample MR results further confirmed the causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.06, 95% confidence interval 0 to 0.13, P = 0.06).
Conclusions
Our results may help the future development of novel intervention approaches for preventing or alleviating loss of SMM.
The survival and development of a semi‐allogeneic fetus during pregnancy require the involvement of a series of cytokines and immune cells. Chemokines are a type of special cytokine those were ...originally described as having a role in leukocyte trafficking. CXC chemokine ligand (CXCL) 16 is a member of the chemokine family, and CXC chemokine receptor (CXCR) 6 is its sole receptor. Emerging evidence has shown that CXCL16/CXCR6 is expressed at the maternal‐fetal interface, by cell types that include trophoblast cells, decidual stroma cells, and decidual immune cells (eg, monocytes, γδT cells, and natural killer T (NKT) cells). The regulation of expression of CXCL16 is quite complex, and this process involves a multitude of factors. CXCL16 exerts a critical role in the establishment of a successful pregnancy through a series of molecular interactions at the maternal‐fetal interface. However, an abnormal expression of CXCL16 is associated with certain pathological states associated with pregnancy, including recurrent miscarriage, pre‐eclampsia, and gestational diabetes mellitus (GDM). In the present review, the expression and pleiotropic roles of CXCL16 under conditions of physiological and pathological pregnancy are systematically discussed.
Background
The left-sided and right-sided colon cancer (LCCs and RCCs, respectively) have unique molecular features and clinical heterogeneity. This study aimed to identify the characteristics of ...immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits.
Methods
The independent gene datasets, corresponding somatic mutation and clinical information were collected from The Cancer Genome Atlas and Gene Expression Omnibus. The ICI contents were evaluated by “ESTIMATE” and “CIBERSORT.” We performed two computational algorithms to identify the ICI landscape related to prognosis and found the unique infiltration characteristics. Next, principal component analysis was conducted to construct ICI score based on three ICI patterns. We analyzed the correlation between ICI score and tumor mutation burden (TMB), and stratified patients into prognostic-related high- and low- ICI score groups (HSG and LSG, respectively). The role of ICI scores in the prediction of therapeutic benefits was investigated by "pRRophetic" and verified by Immunophenoscores (IPS) (TCIA database) and an independent immunotherapy cohort (IMvigor210). The key genes were preliminary screened by weighted gene co-expression network analysis based on ICI scores. And they were further identified at various levels, including single cell, protein and immunotherapy response. The predictive ability of ICI score for prognosis was also verified in IMvigor210 cohort.
Results
The ICI features with a better prognosis were marked by high plasma cells, dendritic cells and mast cells, low memory CD4
+
T cells, M0 macrophages, M1 macrophages, as well as M2 macrophages. A high ICI score was characterized by an increased TMB and genomic instability related signaling pathways. The prognosis, sensitivities of targeted inhibitors and immunotherapy, IPS and expression of immune checkpoints were significantly different in HSG and LSG. The genes identified by ICI scores and various levels included CA2 and TSPAN1.
Conclusion
The identification of ICI subtypes and ICI scores will help gain insights into the heterogeneity in LCC and RCC, and identify patients probably benefiting from treatments. ICI scores and the key genes could serve as an effective biomarker to predict prognosis and the sensitivity of immunotherapy.
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•The basic concept of non-pneumatic tires and the research status of non-pneumatic tires are systematically reviewed.•Research on the structure, materials, mechanical characteristics, ...prevailing forming technologies of non-pneumatic tires is summarized.•The idea of applying intelligent material and structure to non-pneumatic tires is creatively proposed.•This paper concludes the advantages and disadvantages of non -pneumatic tires, and summarizes the development trend.
Non-pneumatic tyre technology can overcome the safety problems of traditional pneumatic tyres. Hence, it is expected to improve driving safety significantly. Accordingly, in recent years, this technology has received extensive attention. This paper reviews the status of research of non-pneumatic tyres and discusses their development trends. Initially, the fundamental concept of non-pneumatic tyres is introduced, and their structural characteristics are described in detail. Subsequently, the research progress on the material properties of non-pneumatic tyre components is summarised. The research results on the mechanical properties of non-pneumatic tyres are recapitulated in terms of vertical mechanical, longitudinal mechanical, lateral mechanical, grounding, vibration, and fatigue characteristics. Moreover, the advantages and disadvantages of non-pneumatic tyres are analysed. Three prevailing forming technologies and tyre performance tests are discussed. The application of intelligent materials and structures to non-pneumatic tyres is proposed for these tyres to be lightweight, functional, and intelligent. Finally, the technical problems that must be resolved in the study of non-pneumatic tyres and the anticipated development trends are presented in this paper.
Surface organic ligands play a critical role in stabilizing atomically precise metal nanoclusters in solutions. However, it is still challenging to prepare highly robust ligated metal nanoclusters ...that are surface‐active for liquid‐phase catalysis without any pre‐treatment. Now, an N‐heterocyclic carbene‐stabilized Au25 nanocluster with high thermal and air stabilities is presented as a homogenous catalyst for cycloisomerization of alkynyl amines to indoles. The nanocluster, characterized as Au25(iPr2‐bimy)10Br72+ (iPr2‐bimy=1,3‐diisopropylbenzimidazolin‐2‐ylidene) (1), was synthesized by direct reduction of AuSMe2Cl and iPr2‐bimyAuBr with NaBH4 in one pot. X‐ray crystallization analysis revealed that the cluster comprises two centered Au13 icosahedra sharing a vertex. Cluster 1 is highly stable and can survive in solution at 80 °C for 12 h, which is superior to Au25 nanoclusters passivated with phosphines or thiols. DFT computations reveal the origins of both electronic and thermal stability of 1 and point to the probable catalytic sites. This work provides new insights into the bonding capability of N‐heterocyclic carbene to Au in a cluster, and offers an opportunity to probe the catalytic mechanism at the atomic level.
An atomically precise N‐heterocyclic carbene‐stabilized Au25 nanocluster is successfully synthesized in a one‐pot reaction. It exhibits much higher thermal stability in the solution form compared to Au25 protected by thiol or phosphine ligands. The cluster displays excellent catalytic activity in the cycloisomerization of alkynyl amine as a homogeneous catalyst.
Fat mass and obesity-associated gene (FTO) is a member of the Fe (II)- and oxoglutarate-dependent AlkB dioxygenase family and is linked to both obesity and intellectual disability. The role of FTO in ...neurodevelopment and neurogenesis, however, remains largely unknown. Here we show that FTO is expressed in adult neural stem cells and neurons and displays dynamic expression during postnatal neurodevelopment. The loss of FTO leads to decreased brain size and body weight. We find that FTO deficiency could reduce the proliferation and neuronal differentiation of adult neural stem cells in vivo, which leads to impaired learning and memory. Given the role of FTO as a demethylase of N6-methyladenosine (m6A), we went on to perform genome-wide m6A profiling and observed dynamic m6A modification during postnatal neurodevelopment. The loss of FTO led to the altered expression of several key components of the brain derived neurotrophic factor pathway that were marked by m6A. These results together suggest FTO plays important roles in neurogenesis, as well as in learning and memory.
The survival and development of a semi-allogenic fetus during pregnancy require special immune tolerance microenvironment at the maternal fetal interface. During the establishment of a successful ...pregnancy, the endometrium undergoes a series of changes, and the extracellular matrix (ECM) breaks down and remodels. Collagen is one of the most abundant ECM. Emerging evidence has shown that collagen and its fragment are expressed at the maternal fetal interface. The regulation of expression of collagen is quite complex, and this process involves a multitude of factors. Collagen exerts a critical role during the successful pregnancy. In addition, the abnormal expressions of collagen and its fragments are associated with certain pathological states associated with pregnancy, including recurrent miscarriage, diabetes mellitus with pregnancy, preeclampsia and so on. In this review, the expression and potential roles of collagen under conditions of physiological and pathological pregnancy are systematically discussed.
DNA methylation is an important heritable epigenetic mark that plays a crucial role in transcriptional regulation and the pathogenesis of various human disorders. The commonly used DNA methylation ...measurement approaches, e.g., Illumina Infinium HumanMethylation-27 and -450 BeadChip arrays (27 K and 450 K arrays) and reduced representation bisulfite sequencing (RRBS), only cover a small proportion of the total CpG sites in the human genome, which considerably limited the scope of the DNA methylation analysis in those studies.
We proposed a new computational strategy to impute the methylation value at the unmeasured CpG sites using the mixture of regression model (MRM) of radial basis functions, integrating information of neighboring CpGs and the similarities in local methylation patterns across subjects and across multiple genomic regions. Our method achieved a better imputation accuracy over a set of competing methods on both simulated and empirical data, particularly when the missing rate is high. By applying MRM to an RRBS dataset from subjects with low versus high bone mineral density (BMD), we recovered methylation values of ~ 300 K CpGs in the promoter regions of chromosome 17 and identified some novel differentially methylated CpGs that are significantly associated with BMD.
Our method is well applicable to the numerous methylation studies. By expanding the coverage of the methylation dataset to unmeasured sites, it can significantly enhance the discovery of novel differential methylation signals and thus reveal the mechanisms underlying various human disorders/traits.
Multi-omics studies, which explore the interactions between multiple types of biological factors, have significant advantages over single-omics analysis for their ability to provide a more holistic ...view of biological processes, uncover the causal and functional mechanisms for complex diseases, and facilitate new discoveries in precision medicine. However, omics datasets often contain missing values, and in multi-omics study designs it is common for individuals to be represented for some omics layers but not all. Since most statistical analyses cannot be applied directly to the incomplete datasets, imputation is typically performed to infer the missing values. Integrative imputation techniques which make use of the correlations and shared information among multi-omics datasets are expected to outperform approaches that rely on single-omics information alone, resulting in more accurate results for the subsequent downstream analyses. In this review, we provide an overview of the currently available imputation methods for handling missing values in bioinformatics data with an emphasis on multi-omics imputation. In addition, we also provide a perspective on how deep learning methods might be developed for the integrative imputation of multi-omics datasets.
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