Biology subjects

Kawakami, E.

Publications and source records attributed to Kawakami, E..

11 recordsLinked to original sources

bioRxiv2026

CATaN maps gene regulatory programs that shape genetic risk across complex diseases

Causal variants of complex traits are enriched at transcription factor (TF) binding sites and are thought to contribute to pathology by disrupting TF activity and thereby causing transcriptome dysregulation. However, existing approaches typically address TF-mediated gene regulatory networks (TF-GRNs) and transcriptomes separately, and methods that jointly leverage both to systematically assess disease heritability remain limited. We aimed to develop a framework that jointly leverages TF-GRNs and transcriptomes to assess disease heritability. Here, we constructed a matrix encoding TF-GRNs and developed an unsupervised analytical pipeline, Canonical correlation Analysis of Transcriptome and TF-gene regulatory Networks (CATaN). CATaN applies canonical correlation analysis (CCA) to extract canonical correlation (CC) components, i.e., shared variation components between transcriptomes and TF-GRNs, and converts them into genome-wide functional annotation scores connected to stratified LD score regression (S-LDSC) for heritability analysis. We applied CATaN to eight datasets, including 19,198 bulk samples and 611,772 single cells from human and mouse sources, identifying 588 CC components that are significantly enriched for SNP heritability across 69 complex traits. Notably, functional annotation tracks based on these TF-GRNs are distinct from transcriptome signatures prioritized by LDSC-SEG, with greater heritability enrichment for a subset of traits. Finally, we suggest that CATaN may help prioritize candidate causal variants for experimental fine-mapping using genome editing. Together, integrating TF-GRNs with transcriptomes reveals disease-relevant regulatory programs that are not fully captured by transcriptome-based analyses alone.

genetics↗

bioRxiv2026

A chromatin relay from AIRE to ETS transcription factors sustains peripheral antigen expression in the thymic mimetic cells to ensure central tolerance.

Medullary thymic epithelial cells (mTECs) establish central tolerance by expressing a diverse repertoire of peripheral tissue-specific antigens (TSAs). This diversity is regulated not only by the transcriptional regulator AIRE, but also by lineage-defining factors in tissue-mimetic, AIRE-negative descendants of Aire mTECs (post-Aire mimetic TECs). However, whether and how prior AIRE activity contributes to TSA expression in post-AIRE mimetic TECs remains unclear. Here, we identify the ETS transcription factors, EHF and ELF3, as key regulators that sustain AIRE-primed gene expression in these cells. EHF and ELF3 preferentially bind distal genomic regions which are rendered accessible in advance by AIRE. Combined loss of EHF and ELF3 disrupts expression of AIRE-regulated genes expressed in mimetic TECs, leading to tissue-selective autoimmunity. Our findings reveal a relay mechanism in which AIRE primes chromatin for ETS factors to maintain TSA expression in post-AIRE mimetic TECs, thereby safeguarding self-tolerance.

immunology↗

bioRxiv2025

A cattle-derived human H5N1 isolate suppresses innate immunity despite efficient replication in human respiratory organoids

The H5N1 high pathogenicity avian influenza virus (HPAIV) of clade 2.3.4.4b, which spreads globally via wild birds, has become a major public health concern because it can infect a variety of mammals, including humans. In 2024, infection of dairy cattle with H5N1 HPAIV clade 2.3.4.4b was confirmed in the United States, and subsequent human cases were reported. Although these viruses are highly pathogenic in animal models, human infections have generally been mild, revealing a striking discrepancy. Here, we characterized the cattle-derived human H5N1 isolate A/Texas/37/2024 (TX37-H5N1) using three-dimensional human respiratory organoids derived from induced pluripotent stem (iPS) cells. Despite efficient replication, TX37-H5N1 induced minimal interferon and inflammatory cytokine responses. Bulk and single-cell RNA sequencing revealed reduced STAT1-mediated transcriptional activity in TX37-H5N1-infected organoids compared to the historic H5N1 human isolate A/Vietnam/1203/2004. These findings suggest that TX37-H5N1 fails to trigger the strong innate responses, including robust cytokine production, that are typically associated with severe H5N1 disease and are thought to contribute to cytokine storm-medicated pathogenesis. This attenuated response may help explain the discrepancy between the high pathogenicity of TX37-H5N1 in animal models and its mild clinical presentation in humans. While zoonotic influenza risk is often assessed using cell lines or animal models, our study highlights the value of using human respiratory organoids to evaluate human-specific virus-host interactions. This platform provides a complementary tool for assessing the risk of emerging avian influenza viruses. HighlightsO_LIHuman respiratory organoids were used to model zoonotic B3.13 H5N1 infections. C_LIO_LIA cattle-derived human isolate, TX37-H5N1, replicated more efficiently than historical VN1203-H5N1. C_LIO_LITX37-H5N1 suppressed STAT-IRF-mediated innate immune responses. C_LIO_LITX37-H5N1 was sensitive to baloxavir and oseltamivir but less sensitive to favipiravir. C_LIO_LIHuman respiratory organoids offer a complementary platform for zoonotic influenza risk assessment. C_LI In briefOur study used human iPSC-derived respiratory organoids to investigate the mild clinical presentation of zoonotic B3.13 H5N1 viruses. We found that TX37-H5N1 replicates efficiently but suppresses innate immune responses, providing mechanistic insight into species-specific pathogenesis and highlighting the utility of human organoids for zoonotic risk assessment.

microbiology↗

bioRxiv2025

Uncertainty-aware transcription factor activity and perturbation inference without additional training

Understanding how transcription factors (TFs) control gene expression is essential for deciphering cellular regulatory programs. However, estimating TF activity remains challenging. Current methods rely on either broad TF-target databases, which increase false positives, or on curated sets with limited coverage. Most methods lack uncertainty quantification. Here, we introduce TFActProfiler, an integrated resource and computational framework that learns signed TF-mRNA effects by pretraining on prior TF-mRNA interaction knowledge and large RNA-seq atlases. Given an expression profile as input, TFActProfiler infers per-sample TF activity together with a confidence score that quantifies agreement between predicted and observed mRNA levels. Across TF knockdown datasets spanning multiple human cell types, TFActProfiler consistently improves TF activity inference over approaches based on unfiltered priors or narrowly curated target sets while retaining broad TF and mRNA coverage. The learned effect map further enables training-free prediction of transcriptome responses to TF perturbations. By coupling TF activity inference with training-free perturbation modeling and confidence estimates, TFActProfiler offers a tool for dissecting regulatory programs across diverse cellular states.

bioinformatics↗

bioRxiv2024

Self-Organization of Sinusoidal Vessels in Pluripotent Stem Cell-derived Human Liver Bud Organoids

The induction of tissue-specific vessels in in vitro living tissue systems remains challenging. Here, we directly differentiated human pluripotent stem cells into CD32b+ putative liver sinusoidal progenitors (iLSEP) by dictating developmental pathways. By devising an inverted multilayered air-liquid interface (IMALI) culture, hepatic endoderm, septum mesenchyme, arterial and sinusoidal quadruple progenitors self-organized to generate and sustain hepatocyte-like cells neighbored by divergent endothelial subsets composed of CD32blowCD31high, LYVE1+STAB1+CD32bhighCD31lowTHBD-vWF-, and LYVE1-THBD+vWF+ cells. Wnt2 mediated sinusoidal-to-hepatic intercellular crosstalk potentiates hepatocyte differentiation and branched endothelial network formation. Intravital imaging revealed iLSEP developed fully patent human vessels with functional sinusoid-like features. Organoid-derived hepatocyte- and sinusoid-derived coagulation factors enabled correction of in vitro clotting time with Factor V, VIII, IX, and XI deficient patients plasma and rescued the severe bleeding phenotype in hemophilia A mice upon transplantation. Advanced organoid vascularization technology allows for interrogating key insights governing organ-specific vessel development, paving the way for coagulation disorder therapeutics.

developmental biology↗

bioRxiv2023

Dimension reduction of microbiome data linked Bifidobacterium to allergic rhinitis

Dimension reduction has been used to visualise the distribution of multidimensional microbiome data, but the composite variables calculated by the dimension reduction methods have not been widely used to investigate the relationship of the human gut microbiome with lifestyle and disease. In the present study, we applied several dimension reduction methods, including principal component analysis (PCA), principal coordinate analysis (PCoA), non-metric multidimensional scaling (NMDS), and non-negative matrix factorization (NMF), to a microbiome dataset from 186 subjects with symptoms of AR and 106 controls. All the dimension reduction methods supported that the enterotype clusters were overlapped in the dimension reduction plots, and that the distribution of microbial data points appeared to be continuous rather than discrete. Comparison of the composite variables calculated from the different dimension reduction methods showed that the characteristics of the composite variables differed between the dimension reduction methods. The second composite variable calculated from PCoA was significantly associated with the intake of several nutrients, including omega-3 polyunsaturated fatty acids, and the risk of AR. The composite variable was also correlated with the relative abundance of Bifidobacterium, and thus, Bifidobacterium was related to the risk of AR and intake of several nutrients through dimension reduction. Our results highlight the usefulness of the dimension reduction methods for investigating the association of microbial composition with lifestyle and disease in clinical research.

microbiology↗

bioRxiv2022

Prediction of elimination of intrahepatic cccDNA in hepatitis B virus-infected patients by a combination of noninvasive viral markers

Evaluation of intrahepatic covalently closed circular DNA (cccDNA) is a key for searching an elimination of hepatitis B virus (HBV) infection. HBV RNA and HBV core-related antigen have been proposed as surrogate markers for evaluating cccDNA activity, although they do not necessarily estimate the amount of cccDNA. Here, we developed a novel multiscale mathematical model describing intra- and inter-cellular viral propagation, based on the experimental quantification data in both HBV-infected cell culture and humanized mouse models. We applied it to HBV-infected patients under treatment and developed a model which can predict intracellular HBV dynamics only by use of noninvasive extracellular surrogate biomarkers. Importantly, the model prediction of the amount of cccDNA in patients over time was confirmed to be well-correlated with the liver biopsy data. Thus, our noninvasive method enables to predict the amount of cccDNA in patients and contributes to determining the treatment endpoint required for elimination of intrahepatic cccDNA.

microbiology↗

bioRxiv2021

Multiple nutritional and gut microbial factors associated with allergic rhinitis: the Hitachi Health Study

Several studies suggest the involvement of dietary habits and gut microbiome in allergic diseases. However, little is known about the nutritional and gut microbial factors associated with the risk of allergic rhinitis (AR). We recruited 186 apparently healthy workers with symptoms of AR and 106 controls at the Hitachi Health Care Center, Japan. The habitual consumption of 42 selected nutrients were examined using the brief-type self-administered diet history questionnaire. Faecal samples were collected and subjected to amplicon sequencing of the 16S ribosomal RNA gene hypervariable regions. Association analysis revealed that four nutrients (retinol, vitamin A, cryptoxanthin, and copper) were negatively associated with AR. Among 40 genera examined, relative abundance of Prevotella and Escherichia were associated with AR. Furthermore, significant statistical interactions were observed between retinol and Prevotella. The age- and sex-adjusted odds of AR were 25-fold lower in subjects with high retinol intake and high Prevotella abundance compared to subjects with low retinol intake and low Prevotella abundance. Our data provide insights into complex interplay between dietary nutrients, gut microbiome, and the development of AR.

microbiology↗

bioRxiv2020

In silico integration of thousands of epigenetic datasets into 707 cell type regulatory annotations improves the trans-ethnic portability of polygenic risk scores

Poor trans-ethnic portability of polygenic risk score (PRS) models is a critical issue that may be partially due to limited knowledge of causal variants shared among populations. Hence, leveraging noncoding regulatory annotations that capture genetic variation across populations has the potential to enhance the trans-ethnic portability of PRS. To this end, we constructed a unique resource of 707 cell-type-specific IMPACT regulatory annotations by aggregating 5,345 public epigenetic datasets to predict binding patterns of 142 cell-type-regulating transcription factors across 245 cell types. With this resource, we partitioned the common SNP heritability of diverse polygenic traits and diseases from 111 GWAS summary statistics of European (EUR, average N=180K) and East Asian (EAS, average N=157K) origin. For 95 traits, we were able to identify a single IMPACT annotation most strongly enriched for trait heritability. Across traits, these annotations captured an average of 43.3% of heritability (se = 13.8%) with the top 5% of SNPs. Strikingly, we observed highly concordant polygenic trait regulation between populations: the same regulatory annotations captured statistically indistinguishable SNP heritability (fitted slope = 0.98, se = 0.04). Since IMPACT annotations capture both large and consistent proportions of heritability across populations, prioritizing variants in IMPACT regulatory elements may improve the trans-ethnic portability of PRS. Indeed, we observed that EUR PRS models more accurately predicted 21 tested phenotypes of EAS individuals when variants were prioritized by key IMPACT tracks (49.9% mean relative increase in R2). Notably, the improvement afforded by IMPACT was greater in the trans-ethnic EUR-to-EAS PRS application than in the EAS-to-EAS application (47.3% vs 20.9%, P < 1.7e-4). Overall, our study identifies a crucial role for functional annotations such as IMPACT to improve the trans-ethnic portability of genetic data, and this has important implications for future risk prediction models that work across populations.

genetics↗

bioRxiv2019

Large scale genome-wide association study in a Japanese population identified 45 novel susceptibility loci for 22 diseases

INTRODUCTORY PARAGRAPHThe overwhelming majority of participants in current genetic studies are of European ancestry1-3, limiting our genetic understanding of complex disease in non-European populations. To address this, we aimed to elucidate polygenic disease biology in the East Asian population by conducting a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 383 independent signals in 331 loci for 30 diseases, among which 45 loci were novel (P < 5 x 10-8). Compared with known variants, novel variants have lower frequency in European populations but comparable frequency in East Asian populations, suggesting the advantage of this study in discovering these novel variants. Three novel signals were in linkage disequilibrium (r2 > 0.6) with missense variants which are monomorphic in European populations (1000 Genomes Project) including rs11235604(p.R220W of ATG16L2, a autophagy-related gene) associated with coronary artery disease. We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, andidentified 378 significant enrichments across nine diseases (FDR < 0.05) (e.g. NF-{kappa}B for immune-related diseases). This large-scale GWAS in a Japanese population provides insights into the etiology of common complex diseases and highlights the importance of performing GWAS in non-European populations.

genetics↗

bioRxiv2018

Network-guided Discovery of Influenza Virus Replication Host Factors

The position of host factors required for viral replication within a human protein-protein interaction (PPI) network can be exploited to identify drug targets that are robust to drug-mediated selective pressure. Host factors can physically interact with viral proteins, be a component of pathways regulated by viruses (where proteins themselves do not interact with viral proteins) or be required for viral replication but unregulated by viruses. Here, we demonstrate a method of combining a human PPI network with virus-host protein interaction data to improve antiviral drug discovery for influenza viruses by identifying target host proteins. Network analysis shows that influenza virus proteins physically interact with host proteins in network positions significant for information flow. We have isolated a subnetwork of the human PPI network which connects virus-interacting host proteins to host factors that are important for influenza virus replication without physically interacting with viral proteins. The subnetwork is enriched for signaling and immune processes. Selecting proteins based on network topology within the subnetwork, we performed an siRNA screen to determine if the subnetwork was enriched for virus replication host factors and if network position within the subnetwork offers an advantage in prioritization of drug targets to control influenza virus replication. We found that the subnetwork is highly enriched for target host proteins - more so than the set of host factors that physically interact with viral proteins. Our findings demonstrate that network positions are a powerful predictor to guide antiviral drug candidate prioritization.\n\nIMPORTANCEIntegrating virus-host interactions with host protein-protein interactions, we have created a method using these established network practices to identify host factors (i.e. proteins) that are likely candidates for antiviral drug targeting. We demonstrate that interaction cascades between host proteins that directly interact with viral proteins and host factors that are important to influenza replication are enriched for signaling and immune processes. Additionally, we show that host proteins that interact with viral proteins are in network locations of power. Finally, we demonstrate a new network methodology to predict novel host factors and validate predictions with an siRNA screen. Our results show that integrating virus-host proteins interactions is useful in the identification of antiviral drug target candidates.

systems biology↗