TRAITER: Transformer-guided diagnosis and prognosis of heart failure using cell nuclear morphology and DNA damage marker.

MOTIVATION: Heart failure (HF), a major cause of morbidity and mortality, necessitates precise diagnostic and prognostic methods. RESULTS: This study presents a novel deep learning approach, Transformer-based Analysis of Images of Tissue for Effective Remedy (TRAITER), for HF diagnosis and prognosis. Employing image segmentation techniques and a Vision Transformer, TRAITER predicts HF likelihood from cardiac tissue cell nuclear morphology images and the potential for left ventricular reverse remodeling (LVRR) from dual-stained images with cell nuclei and DNA damage markers. In HF prediction using 31,158 images from 9 patients, TRAITER achieved 83.1% accuracy. For LVRR prediction with 231,840 images from 46 patients, TRAITER attained 84.2% accuracy for individual images and 92.9% for individual patients. TRAITER outperformed other neural network models in terms of receiver operating characteristics, and precision-recall curves. Our method promises to advance personalized HF medicine decision-making. AVAILABILITY: The source code and data are available at the following link: Https://github.com/HamanoLaboratory/predict-of-HF-and-LVRR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Galectin-10 in serum extracellular vesicles reflects asthma pathophysiology.

BACKGROUND: Novel biomarkers (BMs) are urgently needed for bronchial asthma (BA) with various phenotypes and endotypes. OBJECTIVE: We sought to identify novel BMs reflecting tissue pathology from serum extracellular vesicles (EVs). METHODS: We performed data-independent acquisition of serum EVs from 4 healthy controls, 4 noneosinophilic asthma (NEA) patients, and 4 eosinophilic asthma (EA) patients to identify novel BMs for BA. We confirmed EA-specific BMs via data-independent acquisition validation in 61 BA patients and 23 controls. To further validate these findings, we performed data-independent acquisition for 6 patients with chronic rhinosinusitis without nasal polyps and 7 patients with chronic rhinosinusitis with nasal polyps. RESULTS: We identified 3032 proteins, 23 of which exhibited differential expression in EA. Ingenuity pathway analysis revealed that protein signatures from each phenotype reflected disease characteristics. Validation revealed 5 EA-specific BMs, including galectin-10 (Gal10), eosinophil peroxidase, major basic protein, eosinophil-derived neurotoxin, and arachidonate 15-lipoxygenase. The potential of Gal10 in EVs was superior to that of eosinophils in terms of diagnostic capability and detection of airway obstruction. In rhinosinusitis patients, 1752 and 8413 proteins were identified from EVs and tissues, respectively. Among 11 BMs identified in EVs and tissues from patients with chronic rhinosinusitis with nasal polyps, 5 (including Gal10 and eosinophil peroxidase) showed significant correlations between EVs and tissues. Gal10 release from EVs was implicated in eosinophil extracellular trapped cell death in vitro and in vivo. CONCLUSION: Novel BMs such as Gal10 from serum EVs reflect disease pathophysiology in BA and may represent a new target for liquid biopsy approaches.

Network-based identification of diagnosis-specific trans-omic biomarkers via integration of multiple omics data.

The integration of multiple omics data promises to reveal new insights into the pathogenic mechanisms of complex human diseases, with the potential to identify avenues for the development of targeted therapies for disease subtypes. However, the extraction of diagnostic/disease-specific biomarkers from multiple omics data with biological pathway knowledge is a challenging issue in precision medicine. In this paper, we present a novel computational method to identify diagnosis-specific trans-omic biomarkers from multiple omics data. In the algorithm, we integrated multi-class sparse canonical correlation analysis (MSCCA) and molecular pathway analysis in order to derive discriminative molecular features that are correlated across different omics layers. We applied our proposed method to analyzing proteome and metabolome data of heart failure (HF), and extracted trans-omic biomarkers for HF subtypes; specifically, ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM). We were able to detect not only individual proteins that were previously reported from single-omics studies but also correlated protein-metabolite pairs characteristic of HF disease subtypes. For example, we identified hexokinase1(HK1)-d-fructose-6-phosphate as a paired trans-omic biomarker for DCM, which could significantly perturb amino-sugar metabolism. Our proposed method is expected to be useful for various applications in precision medicine.

DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion.

MOTIVATION: Direct reprogramming (DR) is a process that directly converts somatic cells to target cells. Although DR via small molecules is safer than using transcription factors (TFs) in terms of avoidance of tumorigenic risk, the determination of DR-inducing small molecules is challenging. RESULTS: Here we present a novel in silico method, DIRECTEUR, to predict small molecules that replace TFs for DR. We extracted DR-characteristic genes using transcriptome profiles of cells in which DR was induced by TFs, and performed a variant of simulated annealing to explore small molecule combinations with similar gene expression patterns with DR-inducing TFs. We applied DIRECTEUR to predicting combinations of small molecules that convert fibroblasts into neurons or cardiomyocytes, and were able to reproduce experimentally verified and functionally related molecules inducing the corresponding conversions. The proposed method is expected to be useful for practical applications in regenerative medicine. AVAILABILITY AND IMPLEMENTATION: The code and data are available at the following link: https://github.com/HamanoLaboratory/DIRECTEUR.git.

Myocardial DNA Damage Predicts Heart Failure Outcome in Various Underlying Diseases.

BACKGROUND: Reliable predictors of treatment efficacy in heart failure have been long awaited. DNA damage has been implicated as a cause of heart failure. OBJECTIVES: The purpose of this study was to investigate the association of DNA damage in myocardial tissue with treatment response and prognosis of heart failure. METHODS: The authors performed immunostaining of DNA damage markers poly(ADP-ribose) (PAR) and γ-H2A.X in endomyocardial biopsy specimens from 175 patients with heart failure with reduced ejection fraction (HFrEF) of various underlying etiologies. They calculated the percentage of nuclei positive for each DNA damage marker (%PAR and %γ-H2A.X). The primary outcome was left ventricular reverse remodeling (LVRR) at 1 year, and the secondary outcome was a composite of cardiovascular death, heart transplantation, and ventricular assist device implantation. RESULTS: Patients who did not achieve LVRR after the optimization of medical therapies presented with significantly higher %PAR and %γ-H2A.X. The ROC analysis demonstrated good performance of both %PAR and %γ-H2A.X for predicting LVRR (AUCs: 0.867 and 0.855, respectively). There was a negative correlation between the mean proportion of DNA damage marker-positive nuclei and the probability of LVRR across different underlying diseases. In addition, patients with higher %PAR or %γ-H2A.X had more long-term clinical events (PAR HR: 1.63 [95% CI: 1.31-2.01]; P < 0.001; γ-H2A.X HR: 1.48 [95% CI: 1.27-1.72]; P < 0.001). CONCLUSIONS: DNA damage determines the consequences of human heart failure. Assessment of DNA damage is useful to predict treatment efficacy and prognosis of heart failure patients with various underlying etiologies.

Bioinformatics Analysis of the Molecular Networks Associated with the Amelioration of Aberrant Gene Expression by a Tyr-Trp Dipeptide in Brains Treated with the Amyloid-ß Peptide.

Short-chain peptides derived from various protein sources have been shown to exhibit diverse bio-modulatory and health-promoting effects in animal experiments and human trials. We recently reported that the oral administration of the Tyr-Trp (YW) dipeptide to mice markedly enhances noradrenaline metabolism in the brain and ameliorates the working-memory deficits induced by the ß-amyloid 25-35 peptide (Aß25-35). In the current study, we performed multiple bioinformatics analyses of microarray data from Aß25-35/YW-treated brains to determine the mechanism underlying the action of YW in the brain and to infer the molecular mechanisms and networks involved in the protective effect of YW in the brain. We found that YW not only reversed inflammation-related responses but also activated various molecular networks involving a transcriptional regulatory system, which is mediated by the CREB binding protein (CBP), EGR-family proteins, ELK1, and PPAR, and the calcium-signaling pathway, oxidative stress tolerance, and an enzyme involved in de novo l-serine synthesis in brains treated with Aß25-35. This study revealed that YW has a neuroprotective effect against Aß25-35 neuropathy, suggesting that YW is a new functional-food-material peptide.

TEAD1 trapping by the Q353R-Lamin A/C causes dilated cardiomyopathy.

Mutations in the LMNA gene encoding Lamin A and C (Lamin A/C), major components of the nuclear lamina, cause laminopathies including dilated cardiomyopathy (DCM), but the underlying molecular mechanisms have not been fully elucidated. Here, by leveraging single-cell RNA sequencing (RNA-seq), assay for transposase-accessible chromatin using sequencing (ATAC-seq), protein array, and electron microscopy analysis, we show that insufficient structural maturation of cardiomyocytes owing to trapping of transcription factor TEA domain transcription factor 1 (TEAD1) by mutant Lamin A/C at the nuclear membrane underlies the pathogenesis of Q353R-LMNA-related DCM. Inhibition of the Hippo pathway rescued the dysregulation of cardiac developmental genes by TEAD1 in LMNA mutant cardiomyocytes. Single-cell RNA-seq of cardiac tissues from patients with DCM with the LMNA mutation confirmed the dysregulated expression of TEAD1 target genes. Our results propose an intervention for transcriptional dysregulation as a potential treatment of LMNA-related DCM.

Reciprocal expression of the immune response genes CXCR3 and IFI44L as module hubs are associated with patient survivals in primary central nervous system lymphoma.

PURPOSE: Here, we investigated expression modules reflecting the reciprocal expression of the cancer microenvironment and immune response-related genes associated with poor prognosis in primary central nervous system lymphoma (PCNSL). METHODS: Weighted gene coexpression network analysis revealed representative modules, including neurogenesis, immune response, anti-virus, microenvironment, gene expression and translation, extracellular matrix, morphogenesis, and cell adhesion in the transcriptome data of 31 PCNSL samples. RESULTS : Gene expression networks were also reflected by protein-protein interaction networks. In particular, some of the hub genes were highly expressed in patients with PCNSL with prognoses as follows: AQP4, SLC1A3, GFAP, CXCL9, CXCL10, GBP2, IFI6, OAS2, IFIT3, DCN, LRP1, and LUM with good prognosis; and STAT1, IFITM3, GZMB, ISG15, LY6E, TGFB1, PLAUR, MMP4, FTH1, PLAU, CSF3R, FGR, POSTN, CCR7, TAS1R3, small ribosomal subunit genes, and collagen type 1/3/4/6 genes with poor prognosis. Furthermore, prognosis prediction formulae were constructed using the Cox proportional-hazards regression model, which demonstrated that the IP-10 receptor gene CXCR3 and type I interferon-induced protein gene IFI44L could predict patient survival in PCNSL. CONCLUSION: These results indicate that the differential expression and balance of immune response and microenvironment genes may be required for PCNSL tumor growth or prognosis prediction, which would help understanding the mechanism of tumorigenesis and potential therapeutic targets in PCNSL.

Small compound-based direct cell conversion with combinatorial optimization of pathway regulations.

MOTIVATION: Direct cell conversion, direct reprogramming (DR), is an innovative technology that directly converts source cells to target cells without bypassing induced pluripotent stem cells. The use of small compounds (e.g. drugs) for DR can help avoid carcinogenic risk induced by gene transfection; however, experimentally identifying small compounds remains challenging because of combinatorial explosion. RESULTS: In this article, we present a new computational method, COMPRENDRE (combinatorial optimization of pathway regulations for direct reprograming), to elucidate the mechanism of small compound-based DR and predict new combinations of small compounds for DR. We estimated the potential target proteins of DR-inducing small compounds and identified a set of target pathways involving DR. We identified multiple DR-related pathways that have not previously been reported to induce neurons or cardiomyocytes from fibroblasts. To overcome the problem of combinatorial explosion, we developed a variant of a simulated annealing algorithm to identify the best set of compounds that can regulate DR-related pathways. Consequently, the proposed method enabled to predict new DR-inducing candidate combinations with fewer compounds and to successfully reproduce experimentally verified compounds inducing the direct conversion from fibroblasts to neurons or cardiomyocytes. The proposed method is expected to be useful for practical applications in regenerative medicine. AVAILABILITY AND IMPLEMENTATION: The code supporting the current study is available at the http://labo.bio.kyutech.ac.jp/~yamani/comprendre. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach.

MOTIVATION: Direct reprogramming involves the direct conversion of fully differentiated mature cell types into various other cell types while bypassing an intermediate pluripotent state (e.g. induced pluripotent stem cells). Cell differentiation by direct reprogramming is determined by two types of transcription factors (TFs): pioneer factors (PFs) and cooperative TFs. PFs have the distinct ability to open chromatin aggregations, assemble a collective of cooperative TFs and activate gene expression. The experimental determination of two types of TFs is extremely difficult and costly. RESULTS: In this study, we developed a novel computational method, TRANSDIRE (TRANS-omics-based approach for DIrect REprogramming), to predict the TFs that induce direct reprogramming in various human cell types using multiple omics data. In the algorithm, potential PFs were predicted based on low signal chromatin regions, and the cooperative TFs were predicted through a trans-omics analysis of genomic data (e.g. enhancers), transcriptome data (e.g. gene expression profiles in human cells), epigenome data (e.g. chromatin immunoprecipitation sequencing data) and interactome data. We applied the proposed methods to the reconstruction of TFs that induce direct reprogramming from fibroblasts to six other cell types: hepatocytes, cartilaginous cells, neurons, cardiomyocytes, pancreatic cells and Paneth cells. We demonstrated that the methods successfully predicted TFs for most cell conversions with high accuracy. Thus, the proposed methods are expected to be useful for various practical applications in regenerative medicine. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at the following website: http://figshare.com/s/b653781a5b9e6639972b. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hepatocyte-Specific Phgdh-Deficient Mice Culminate in Mild Obesity, Insulin Resistance, and Enhanced Vulnerability to Protein Starvation.

l-Serine (Ser) is synthesized de novo from 3-phosphoglycerate via the phosphorylated pathway committed by phosphoglycerate dehydrogenase (Phgdh). A previous study reported that feeding a protein-free diet increased the enzymatic activity of Phgdh in the liver and enhanced Ser synthesis in the rat liver. However, the nutritional and physiological functions of Ser synthesis in the liver remain unclear. To clarify the physiological significance of de novo Ser synthesis in the liver, we generated liver hepatocyte-specific Phgdh KO (LKO) mice using an albumin-Cre driver. The LKO mice exhibited a significant gain in body weight compared to Floxed controls at 23 weeks of age and impaired systemic glucose metabolism, which was accompanied by diminished insulin/IGF signaling. Although LKO mice had no apparent defects in steatosis, the molecular signatures of inflammation and stress responses were evident in the liver of LKO mice. Moreover, LKO mice were more vulnerable to protein starvation than the Floxed mice. These observations demonstrate that Phgdh-dependent de novo Ser synthesis in liver hepatocytes contributes to the maintenance of systemic glucose tolerance, suppression of inflammatory response, and resistance to protein starvation.

Prediction of single-cell mechanisms for disease progression in hypertrophic remodelling by a trans-omics approach.

Heart failure is a heterogeneous disease with multiple risk factors and various pathophysiological types, which makes it difficult to understand the molecular mechanisms involved. In this study, we proposed a trans-omics approach for predicting molecular pathological mechanisms of heart failure and identifying marker genes to distinguish heterogeneous phenotypes, by integrating multiple omics data including single-cell RNA-seq, ChIP-seq, and gene interactome data. We detected a significant increase in the expression level of natriuretic peptide A (Nppa), after stress loading with transverse aortic constriction (TAC), and showed that cardiomyocytes with high Nppa expression displayed specific gene expression patterns. Multiple NADH ubiquinone complex family, which are associated with the mitochondrial electron transport system, were negatively correlated with Nppa expression during the early stages of cardiac hypertrophy. Large-scale ChIP-seq data analysis showed that Nkx2-5 and Gtf2b were transcription factors characteristic of high-Nppa-expressing cardiomyocytes. Nppa expression levels may, therefore, represent a useful diagnostic marker for heart failure.

Transcriptional Activation of Chac1 and Other Atf4-Target Genes Induced by Extracellular l-Serine Depletion is negated with Glycine Consumption in Hepa1-6 Hepatocarcinoma Cells.

Mouse embryonic fibroblasts lacking D-3-phosphoglycerate dehydrogenase (Phgdh), which catalyzes the first step of de novo synthesis of l-serine, are particularly sensitive to depletion of extracellular L-serine. In these cells, depletion of l-serine leads to a rapid reduction of intracellular L-serine, cell growth arrest, and altered expression of a wide variety of genes. However, it remains unclear whether reduced availability of extracellular l-serine elicits such responses in other cell types expressing Phgdh. Here, we show in the mouse hepatoma cell line Hepa1-6 that extracellular l-serine depletion transiently induced transcriptional activation of Atf4-target genes, including cation transport regulator-like protein 1 (Chac1). Expression levels of these genes returned to normal 24 h after l-serine depletion, and were suppressed by the addition of l-serine or glycine in the medium. Extracellular l-serine depletion caused a reduction of extracellular and intracellular glycine levels but maintained intracellular l-serine levels in the cells. Further, Phgdh and serine hydroxymethyltransferase 2 (Shmt2) were upregulated after l-serine depletion. These results led us to conclude that the Atf4-mediated gene expression program is activated by extracellular l-serine depletion in Hepa1-6 cells expressing Phgdh, but is antagonized by the subsequent upregulation of l-serine synthesis, mainly from autonomous glycine consumption.

GSEA-assisted gene signatures valid for combinations of prognostic markers in PCNSL.

Primary central nervous system lymphoma (PCNSL) is a brain malignant non-Hodgkin's B-cell lymphoma. The standard treatments are high-dose methotrexate (MTX)-based chemotherapies and deferred whole brain radiotherapy. However, MTX resistance-dependent global expression and signaling pathway changes and their relationship with prognoses have not yet been elucidated. Here, we conducted a global expression analysis with next-generation sequencing and gene set enrichment analysis (GSEA) in MTX-resistant PCNSL cell lines (HKBML-MTX and TK-MTX) and PCNSL tissues. In rank scores, genes listed in HKBML-MTX and TK-MTX were enriched in PCNSL with poor prognoses. In fold changes, a part of differentially-expressed genes in PCNSL tissues were also detected in HKBML-MTX and TK-MTX cells; FOXD2-AS1 and MMP19 were commonly expressed in both HKBML-MTX and TK-MTX, FABP5 and CD70 were HKBML-MTX-specifically expressed, and CLCN2, HOXB9, INE1, and LRP5L were TK-MTX-specifically expressed, which may provide a combination of prognostic markers on MTX-sensitivities in PCNSL. Additionally, PCNSL subgroups, divided with hierarchical clustering and Kaplan-Meier methods, included twenty commonly expressed genes in both HKBML-MTX and TK-MTX, ten HKBML-MTX-specifically expressed genes, and two TK-MTX-specifically expressed genes. These results suggest that the GSEA-assisted gene signatures can provide a combination for prognostic markers in recurrent PCNSL with MTX resistances.

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm.

MOTIVATION: Genome-wide identification of the transcriptomic responses of human cell lines to drug treatments is a challenging issue in medical and pharmaceutical research. However, drug-induced gene expression profiles are largely unknown and unobserved for all combinations of drugs and human cell lines, which is a serious obstacle in practical applications. RESULTS: Here, we developed a novel computational method to predict unknown parts of drug-induced gene expression profiles for various human cell lines and predict new drug therapeutic indications for a wide range of diseases. We proposed a tensor-train weighted optimization (TT-WOPT) algorithm to predict the potential values for unknown parts in tensor-structured gene expression data. Our results revealed that the proposed TT-WOPT algorithm can accurately reconstruct drug-induced gene expression data for a range of human cell lines in the Library of Integrated Network-based Cellular Signatures. The results also revealed that in comparison with the use of original gene expression profiles, the use of imputed gene expression profiles improved the accuracy of drug repositioning. We also performed a comprehensive prediction of drug indications for diseases with gene expression profiles, which suggested many potential drug indications that were not predicted by previous approaches. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enhanced vulnerability to oxidative stress and induction of inflammatory gene expression in 3-phosphoglycerate dehydrogenase-deficient fibroblasts.

l-Serine (l-Ser) is a necessary precursor for the synthesis of proteins, lipids, glycine, cysteine, d-serine, and tetrahydrofolate metabolites. Low l-Ser availability activates stress responses and cell death; however, the underlying molecular mechanisms remain unclear. l-Ser is synthesized de novo from 3-phosphoglycerate with 3-phosphoglycerate dehydrogenase (Phgdh) catalyzing the first reaction step. Here, we show that l-Ser depletion raises intracellular H2O2 levels and enhances vulnerability to oxidative stress in Phgdh-deficient mouse embryonic fibroblasts. These changes were associated with reduced total glutathione levels. Moreover, levels of the inflammatory markers thioredoxin-interacting protein and prostaglandin-endoperoxide synthase 2 were upregulated under l-Ser-depleted conditions; this was suppressed by the addition of N-acetyl-l-cysteine. Thus, intracellular l-Ser deficiency triggers an inflammatory response via increased oxidative stress, and de novo l-Ser synthesis suppresses oxidative stress damage and inflammation when the external l-Ser supply is restricted.

Microarray data on altered transcriptional program of Phgdh-deficient mouse embryonic fibroblasts caused by ʟ-serine depletion.

Inherent ʟ-Ser deficiency culminates in intrauterine growth retardation, severe malformation of multiple organs particularly the central nervous system, and perinatal or early postnatal death in human and mouse. To uncover the molecular mechanisms underlying the growth-arrested phenotypes of l-Ser deficiency, we compared gene expression profiles of mouse embryonic fibroblasts deficient in 3-phosphoglycerate dehydrogenase (Phgdh), the first enzyme of de novo ʟ-Ser synthetic pathway, between ʟ-Ser-depleted and -supplemented conditions. The datasets (CEL and CHP files) from this study are publicly available on the Gene Expression Omnibus repository (accession number GEO: GSE55687).

Adaptive response to l-serine deficiency is mediated by p38 MAPK activation via 1-deoxysphinganine in normal fibroblasts.

UNLABELLED: Reduced availability of l-serine limits cell proliferation and leads to an adaptation to l-serine-deficient environment, the underlying molecular mechanism of which remain largely unexplored. Genetic ablation of 3-phosphoglycerate dehydrogenase (Phgdh), which catalyzes the first step of de novo l-serine synthesis, led to diminished cell proliferation and the activation of p38 MAPK and stress-activated protein kinase/Jun amino-terminal kinase in mouse embryonic fibroblasts under l-serine depletion. The resultant l-serine deficiency induced cyclin-dependent kinase inhibitor 1a (Cdkn1a; p21) expression, which was mediated by p38 MAPK. Survival of the Phgdh-deficient mouse embryonic fibroblasts was markedly reduced by p38 MAPK inhibition under l-serine depletion, whereas p38 MAPK could be activated by 1-deoxysphinganine, an atypical alanine-derived sphingoid base that was found to accumulate in l-serine-depleted mouse embryonic fibroblasts. These observations provide persuasive evidence that when the external l-serine supply is limited, l-serine synthesized de novo in proliferating cells serves as a metabolic gatekeeper to maintain cell survival and the functions necessary for executing cell cycle progression. DATABASE: Gene Expression Omnibus, accession number GSE55687.