Accelerated dimensionality reduction of single-cell RNA sequencing data with fastglmpca.

Motivated by theoretical and practical issues that arise when applying Principal Components Analysis (PCA) to count data, Townes et al introduced "Poisson GLM-PCA", a variation of PCA adapted to count data, as a tool for dimensionality reduction of single-cell RNA sequencing (RNA-seq) data. However, fitting GLM-PCA is computationally challenging. Here we study this problem, and show that a simple algorithm, which we call "Alternating Poisson Regression" (APR), produces better quality fits, and in less time, than existing algorithms. APR is also memory-efficient, and lends itself to parallel implementation on multi-core processors, both of which are helpful for handling large single-cell RNA-seq data sets. We illustrate the benefits of this approach in two published single-cell RNA-seq data sets. The new algorithms are implemented in an R package, fastglmpca.

A pairwise cytokine code explains the organism-wide response to sepsis.

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the molecular and cellular impact of sepsis across organs remains rudimentary. Here, we characterize the pathogenesis of sepsis by measuring dynamic changes in gene expression across organs. To pinpoint molecules controlling organ states in sepsis, we compare the effects of sepsis on organ gene expression to those of 6 singles and 15 pairs of recombinant cytokines. Strikingly, we find that the pairwise effects of tumor necrosis factor plus interleukin (IL)-18, interferon-gamma or IL-1ß suffice to mirror the impact of sepsis across tissues. Mechanistically, we map the cellular effects of sepsis and cytokines by computing changes in the abundance of 195 cell types across 9 organs, which we validate by whole-mouse spatial profiling. Our work decodes the cytokine cacophony in sepsis into a pairwise cytokine message capturing the gene, cell and tissue responses of the host to the disease.

Adjusting for genetic confounders in transcriptome-wide association studies improves discovery of risk genes of complex traits.

Many methods have been developed to leverage expression quantitative trait loci (eQTL) data to nominate candidate genes from genome-wide association studies. These methods, including colocalization, transcriptome-wide association studies (TWAS) and Mendelian randomization-based methods; however, all suffer from a key problem-when assessing the role of a gene in a trait using its eQTLs, nearby variants and genetic components of other genes' expression may be correlated with these eQTLs and have direct effects on the trait, acting as potential confounders. Our extensive simulations showed that existing methods fail to account for these 'genetic confounders', resulting in severe inflation of false positives. Our new method, causal-TWAS (cTWAS), borrows ideas from statistical fine-mapping and allows us to adjust all genetic confounders. cTWAS showed calibrated false discovery rates in simulations, and its application on several common traits discovered new candidate genes. In conclusion, cTWAS provides a robust statistical framework for gene discovery.

Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions.

We introduce mvSuSiE, a multi-trait fine-mapping method for identifying putative causal variants from genetic association data (individual-level or summary data). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal SNPs. Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multi-trait methods, and uniformly improves on single-trait fine-mapping (SuSiE) in each trait separately. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing the traits and modeling heterogeneous effect sharing patterns, we discovered a much larger number of causal SNPs (>3,000) compared with single-trait fine-mapping, and with narrower credible sets. mvSuSiE also more comprehensively characterized the ways in which the genetic variants affect one or more blood cell traits; 68% of causal SNPs showed significant effects in more than one blood cell type.

Not just fibrotic: endothelial-derived TGFß maintains contractile function and lymphatic muscle phenotype during homeostasis.

Cell-cell communication within the lymphatic vasculature during homeostasis is incompletely detailed. Although many discoveries highlight the pathological roles of transforming growth factor-beta (TGFß) in chronic vascular inflammation and associated fibrosis, only a small amount is known surrounding the role of TGFß-signaling in homeostatic lymphatic function. Here, we discovered that pharmacological blockade of TGFß receptor 1 (TGFßR1) negatively impacts rat mesenteric lymphatic vessel pumping, significantly reducing vessel contractility and surrounding lymphatic muscle coverage. We have identified mesenteric lymphatic endothelial cells themselves as a source of endogenous vascular TGFß and that TGFß production is significantly increased in these cells via activation of a number of functional pattern recognition receptors they express. We show that a continuous supply of TGFß is essential to maintain the contractile phenotype of neighboring lymphatic muscle cells and support this conclusion through in vitro analysis of primary isolated lymphatic muscle cells that undergo synthetic differentiation during 2-D cell culture, a phenomenon that could be effectively rescued by supplementation with recombinant TGFß. Finally, we demonstrate that lymphatic endothelial production of TGFß is regulated, in part, by nitric oxide in a manner we propose is essential to counteract the pathological over-production of TGFß. Taken together, these data highlight the essential role of homeostatic TGFß signaling in the maintenance of lymphatic vascular function and highlight possible deleterious consequences of its inhibition.NEW & NOTEWORTHY The growth factor TGFß is commonly associated with its pathological overproduction during tissue fibrosis rather than its homeostatic functions. We expose the lymphatic endothelium as a source of endogenous TGFß, the impact of its production on the maintenance of surrounding lymphatic muscle cell phenotype, and internally regulated mechanisms of its production. Overall, these results highlight the intricate balance of TGFß-signaling as an essential component of maintaining lymphatic contractile function.

Flow-dependent regulation of rat mesenteric lymphatic vessel contractile response requires activation of endothelial TRPV4 channels.

OBJECTIVES: The objective of our study is to evaluate the involvement of the transient receptor potential vanilloid 4 (TRPV4) in the alteration of lymphatic pumping in response to flow and determine the signaling pathways involved. METHODS: We used immunofluorescence imaging and western blotting to assess TRPV4 expression in rat mesenteric lymphatic vessels. We examined inhibition of TRPV4 with HC067047, nitric oxide synthase (NOS) with L-NNA and cyclooxygenases (COXs) with indomethacin on the contractile response of pressurized lymphatic vessels to flow changes induced by a stepwise increase in pressure gradients, and the functionality of endothelial TRPV4 channels by measuring the intracellular Ca2+ response of primary lymphatic endothelial cell cultures to the selective agonist GSK1016790A. RESULTS: TRPV4 protein was expressed in both the endothelial and the smooth muscle layer of rat mesenteric lymphatics with high endothelial expression around the valve sites. When maintained under constant transmural pressure, most lymphatic vessels displayed a decrease in contraction frequency under conditions of flow and this effect was ablated through inhibition of NOS, COX or TRPV4. CONCLUSIONS: Our findings demonstrate a critical role for TRPV4 in the decrease in contraction frequency induced in lymphatic vessels by increases in flow rate via the production and action of nitric oxide and dilatory prostanoids.

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership.

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

DISSECTING TUMOR TRANSCRIPTIONAL HETEROGENEITY FROM SINGLE-CELL RNA-SEQ DATA BY GENERALIZED BINARY COVARIANCE DECOMPOSITION.

Profiling tumors with single-cell RNA sequencing (scRNA-seq) has the potential to identify recurrent patterns of transcription variation related to cancer progression, and so produce new therapeutically-relevant insights. However, the presence of strong inter-tumor heterogeneity often obscures more subtle patterns that are shared across tumors, some of which may characterize clinically-relevant disease subtypes. Here we introduce a new statistical method to address this problem. We show that this method can help decompose transcriptional heterogeneity into interpretable components - including patient-specific, dataset-specific and shared components relevant to disease subtypes - and that, in the presence of strong inter-tumor heterogeneity, our method can produce more interpretable results than existing widely-used methods. Applied to data from three studies on pancreatic cancer adenocarcinoma (PDAC), our method produces a refined characterization of existing tumor subtypes (e.g. classical vs basal), and identifies a new gene expression program (GEP) that is prognostic of poor survival independent of established prognostic factors such as tumor stage and subtype. The new GEP is enriched for genes involved in a variety of stress responses, and suggests a potentially important role for the integrated stress response in PDAC development and prognosis.

A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes.

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms.

The Bayesian lens and Bayesian blinkers.

I discuss the benefits of looking through the 'Bayesian lens' (seeking a Bayesian interpretation of ostensibly non-Bayesian methods), and the dangers of wearing 'Bayesian blinkers' (eschewing non-Bayesian methods as a matter of philosophical principle). I hope that the ideas may be useful to scientists trying to understand widely used statistical methods (including confidence intervals and [Formula: see text]-values), as well as teachers of statistics and practitioners who wish to avoid the mistake of overemphasizing philosophy at the expense of practical matters. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership.

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

Organism-Wide Analysis of Sepsis Reveals Mechanisms of Systemic Inflammation.

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the impact of sepsis across organs of the body is rudimentary. Here, using mouse models of sepsis, we generate a dynamic, organism-wide map of the pathogenesis of the disease, revealing the spatiotemporal patterns of the effects of sepsis across tissues. These data revealed two interorgan mechanisms key in sepsis. First, we discover a simplifying principle in the systemic behavior of the cytokine network during sepsis, whereby a hierarchical cytokine circuit arising from the pairwise effects of TNF plus IL-18, IFN-γ, or IL-1ß explains half of all the cellular effects of sepsis on 195 cell types across 9 organs. Second, we find that the secreted phospholipase PLA2G5 mediates hemolysis in blood, contributing to organ failure during sepsis. These results provide fundamental insights to help build a unifying mechanistic framework for the pathophysiological effects of sepsis on the body.

Socio-economic and psychosocial determinants of violent discipline among parents in Asia Pacific countries during COVID-19: Focus on disadvantaged populations.

BACKGROUND: Mobility restrictions and economic downfall as a result of the COVID-19 pandemic may increase the risk of child maltreatment, including increased risk for violent discipline use by parents. OBJECTIVE: We examined the socio-economic and psychosocial determinants of violent discipline among parents against children in Asia Pacific countries. PARTICIPANTS & SETTINGS: This secondary data analysis included 7765 parents with children 6-18 years old in eight Asia Pacific countries. METHODS: 24 potential determinants were identified, including household demographic factors, parents' psychosocial status, and livelihood changes. The dependent variable was parental use of violent discipline (physical, severe physical, psycho-social aggression, and any violent discipline). Univariate and multivariable logistic regression analysis was conducted. RESULTS: A total of 41 % of households reported violent discipline. Parental demographic characteristics that were positively related to use of violent discipline were living in rural areas, not being a household head, female sex, age younger than 35 years, and large family size. Poor parental mental health status, loss of job or reduced income due to COVID-19, lack of food at household level, parent engagement in petty trade, and owning a business also predicted violent discipline. Mandatory curfew and receiving pandemic-related education materials were also positive predictors. CONCLUSION: Some socio-demographic factors, economic hardship due to COVID-19, and poor mental health status of parents are associated with the use of violent discipline against children in the Asia Pacific region. These results highlight several potential target areas for child protection interventions by governmental and non-profit organizations, including economic, social, and mental health interventions.

Lymph-derived chemokines direct early neutrophil infiltration in the lymph nodes upon Staphylococcus aureus skin infection.

A large number of neutrophils infiltrate the lymph node (LN) within 4 h after Staphylococcus aureus skin infection (4 h postinfection [hpi]) and prevent systemic S. aureus dissemination. It is not clear how infection in the skin can remotely and effectively recruit neutrophils to the LN. Here, we found that lymphatic vessel occlusion substantially reduced neutrophil recruitment to the LN. Lymphatic vessels effectively transported bacteria and proinflammatory chemokines (i.e., Chemokine [C-X-C motif] motif 1 [CXCL1] and CXCL2) to the LN. However, in the absence of lymph flow, S. aureus alone in the LN was insufficient to recruit neutrophils to the LN at 4 hpi. Instead, lymph flow facilitated the earliest neutrophil recruitment to the LN by delivering chemokines (i.e., CXCL1, CXCL2) from the site of infection. Lymphatic dysfunction is often found during inflammation. During oxazolone (OX)-induced skin inflammation, CXCL1/2 in the LN was reduced after infection. The interrupted LN conduits further disrupted the flow of lymph and impeded its communication with high endothelial venules (HEVs), resulting in impaired neutrophil migration. The impaired neutrophil interaction with bacteria contributed to persistent infection in the LN. Our studies showed that both the flow of lymph from lymphatic vessels to the LN and the distribution of lymph in the LN are critical to ensure optimal neutrophil migration and timely innate immune protection in S. aureus infection.

Mincle-binding DNA aptamer demonstrates therapeutic potential in a model of inflammatory bowel disease.

Pattern recognition receptors such as Mincle (Clec4e) play a significant role in the regulation of inflammation. Enhanced signaling of Mincle through the release of damage-associated molecular patterns during sterile inflammation has been shown to be important in the progression and manifestation of several diseases. A limitation to Mincle-targeted therapeutics is the feasibility of human-scale antibody therapy and the lack of alternative small-molecule inhibitors. Herein, we describe a highly specific neutralizing DNA aptamer targeting Mincle and demonstrate its therapeutic potential. Our data demonstrate that AptMincle selectively binds to both human and mouse Mincle with high affinity and is able to directly target and reduce Mincle activation. AptMincle can specifically reduce trehalose-6,6-dibehenate (TDB)-induced Syk and P65 phosphorylation in vitro in a manner comparable to that of the commercially available neutralizing antibody in vitro. Moreover, a bio-stable modified aptamer, AptMincleDRBL, was successful in reducing disease activity in a dextran sodium sulfate (DSS)-induced model of ulcerative colitis in a dose- and sequence-dependent manner. The results present an alternative, highly specific DNA aptamer with antagonistic function for use in the investigation of Mincle-associated diseases. The data also show the translational potential of Mincle-targeting aptamers as a new category of biologic therapy in the treatment of inflammatory bowel disease (IBD).

Fine-mapping from summary data with the "Sum of Single Effects" model.

In recent work, Wang et al introduced the "Sum of Single Effects" (SuSiE) model, and showed that it provides a simple and efficient approach to fine-mapping genetic variants from individual-level data. Here we present new methods for fitting the SuSiE model to summary data, for example to single-SNP z-scores from an association study and linkage disequilibrium (LD) values estimated from a suitable reference panel. To develop these new methods, we first describe a simple, generic strategy for extending any individual-level data method to deal with summary data. The key idea is to replace the usual regression likelihood with an analogous likelihood based on summary data. We show that existing fine-mapping methods such as FINEMAP and CAVIAR also (implicitly) use this strategy, but in different ways, and so this provides a common framework for understanding different methods for fine-mapping. We investigate other common practical issues in fine-mapping with summary data, including problems caused by inconsistencies between the z-scores and LD estimates, and we develop diagnostics to identify these inconsistencies. We also present a new refinement procedure that improves model fits in some data sets, and hence improves overall reliability of the SuSiE fine-mapping results. Detailed evaluations of fine-mapping methods in a range of simulated data sets show that SuSiE applied to summary data is competitive, in both speed and accuracy, with the best available fine-mapping methods for summary data.

Fine-mapping studies distinguish genetic risks for childhood- and adult-onset asthma in the HLA region.

BACKGROUND: Genome-wide association studies of asthma have revealed robust associations with variation across the human leukocyte antigen (HLA) complex with independent associations in the HLA class I and class II regions for both childhood-onset asthma (COA) and adult-onset asthma (AOA). However, the specific variants and genes contributing to risk are unknown. METHODS: We used Bayesian approaches to perform genetic fine-mapping for COA and AOA (n=9432 and 21,556, respectively; n=318,167 shared controls) in White British individuals from the UK Biobank and to perform expression quantitative trait locus (eQTL) fine-mapping in immune (lymphoblastoid cell lines, n=398; peripheral blood mononuclear cells, n=132) and airway (nasal epithelial cells, n=188) cells from ethnically diverse individuals. We also examined putatively causal protein coding variation from protein crystal structures and conducted replication studies in independent multi-ethnic cohorts from the UK Biobank (COA n=1686; AOA n=3666; controls n=56,063). RESULTS: Genetic fine-mapping revealed both shared and distinct causal variation between COA and AOA in the class I region but only distinct causal variation in the class II region. Both gene expression levels and amino acid variation contributed to risk. Our results from eQTL fine-mapping and amino acid visualization suggested that the HLA-DQA1*03:01 allele and variation associated with expression of the nonclassical HLA-DQA2 and HLA-DQB2 genes accounted entirely for the most significant association with AOA in GWAS. Our studies also suggested a potentially prominent role for HLA-C protein coding variation in the class I region in COA. We replicated putatively causal variant associations in a multi-ethnic cohort. CONCLUSIONS: We highlight roles for both gene expression and protein coding variation in asthma risk and identified putatively causal variation and genes in the HLA region. A convergence of genomic, transcriptional, and protein coding evidence implicates the HLA-DQA2 and HLA-DQB2 genes and HLA-DQA1*03:01 allele in AOA.

Tumor-Draining Lymph Node Reconstruction Promotes B Cell Activation During E0771 Mouse Breast Cancer Growth.

Lymph node metastasis is associated with tumor aggressiveness and poor prognosis in patients. Despite its significance in cancer progression, how immune cells in the tumor-draining lymph node (TDLN) participate in cancer immune regulation remains poorly understood. It has been reported that both anti-tumor and exhausted tumor-specific T cells can be induced in the TDLNs; however, B cell activation and maturation in the TDLN has received far less attention. In our studies using C57BL/6 mouse syngeneic E0771 breast cancer or B16F10 melanoma cell lines, tumor-associated antigens were found colocalized with the follicular dendritic cells (FDCs) in the germinal centers (GCs), where antigen-specific B cell maturation occurs. LN conduits and the subcapsular sinus (SCS) macrophages are two major routes of antigen trafficking to FDCs. Tumor growth induced LN conduit expansion in the B cell zone and disrupted the SCS macrophage layer, facilitating both the entry of tumor-associated antigens into the B cell zone and access to FDCs located in the GCs. Regional delivery of clodronate liposome specifically depleted SCS macrophages in the TDLN, increasing GC formation, and promoting tumor growth. Our study suggests that TDLN reconstruction creates a niche that favors B cell activation and maturation during tumor growth.

The emerging potential of Aptamers as therapeutic agents in infection and inflammation.

Refined from pools of random sequence oligonucleotides, nucleic acid aptamers have been found to bind an almost limitless array of targets, including clinically-relevant proteins. Comparable to their antibody counterparts, aptamers display significant advantages over protein-based therapeutics in part due to their flexibility in chemical modifications, small size, and scalability. Despite the perceived benefits, and amidst the growth of an increasing number of clinically approved nucleic acid-based therapeutics, orthodox biologics remain dominant. Research over the last three decades has identified several aptamers that contain the potential to reshape the medicinal field as both diagnostic tools and treatments. Herein, we provide a tailored overview of promising developments in therapeutic nucleic acid-based aptamers in the treatment of infection and inflammation and their proposed future applications.

The dietary fibre rhamnogalacturonan improves intestinal epithelial barrier function in a microbiota-independent manner.

BACKGROUND AND PURPOSE: Dietary fibre comprises a complex group of polysaccharides that are indigestible but are fermented by gut microbiota, promoting beneficial effects to the intestinal mucosa indirectly through the production of short chain fatty acids. We found that a polysaccharide, rhamnogalacturonan (RGal), from the plant Acmella oleracea, has direct effects on intestinal epithelial barrier function. Our objective was to determine the mechanism whereby RGal enhances epithelial barrier function. EXPERIMENTAL APPROACH: Monolayers of colonic epithelial cell lines (Caco-2, T84) and of human primary cells from organoids were mounted in Ussing chambers to assess barrier function. The cellular mechanism of RGal effects on barrier function was determined using inhibitors of TLR-4 and PKC isoforms. KEY RESULTS: Apically applied RGal (1000 µg ml-1 ) significantly enhanced barrier function as shown by increased transepithelial electrical resistance (TER) and reduced fluorescein isothiocyanate (FITC)-dextran flux in Caco-2, T84 and human primary cell monolayers, and accelerated tight junction reassembly in Caco-2 cells in a calcium switch assay. RGal also reversed the barrier-damaging effects of inflammatory cytokines on FITC-dextran flux and preserved the tight junction distribution of occludin. RGal activated TLR4 in TLR4-expressing HEK reporter cells, an effect that was inhibited by the TLR4 inhibitor, C34. The effect of RGal was also dependent on PKC, specifically the isoforms PKCδ and PKCζ. CONCLUSION AND IMPLICATIONS: RGal enhances intestinal epithelial barrier function through activation of TLR4 and PKC signalling pathways. Elucidation of RGal mechanisms of action could lead to new, dietary approaches to enhance mucosal healing in inflammatory bowel diseases.