SCRN: Single-cell Gene Regulatory Network Identification in Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease, and it consumes considerable medical resources with increasing number of patients every year. Mounting evidence show that the regulatory disruptions altering the intrinsic activity of genes in brain cells contribute to AD pathogenesis. To gain insights into the underlying gene regulation in AD, we proposed a graph learning method, Single-Cell based Regulatory Network (SCRN), to identify the regulatory mechanisms based on single-cell data. SCRN implements the γ-decaying heuristic link prediction based on graph neural networks and can identify reliable gene regulatory networks using locally closed subgraphs. In this work, we first performed UMAP dimension reduction analysis on single-cell RNA sequencing (scRNA-seq) data of AD and normal samples. Then we used SCRN to construct the gene regulatory network based on three well-recognized AD genes (APOE, CX3CR1, and P2RY12). Enrichment analysis of the regulatory network revealed significant pathways including NGF signaling, ERBB2 signaling, and hemostasis. These findings demonstrate the feasibility of using SCRN to uncover potential biomarkers and therapeutic targets related to AD.

Interstitial fibrosis increases the risk of end-stage kidney disease in patients with lupus nephritis.

OBJECTIVE: To evaluate the risk of end-stage kidney disease (ESKD) in lupus nephritis (LN) patients using tubulointerstitial lesion scores. METHODS: Clinical profiles and histopathological presentations of 151 biopsy-proven LN patients were retrospectively examined. Risk factors of ESKD based on characteristics and scoring of their tubulointerstitial lesions (e.g. interstitial inflammation [II], tubular atrophy [TA], and interstitial fibrosis [IF]) were analyzed. RESULTS: The mean age of 151 LN patients was 36 years old, and 136 (90.1%) were female. The LN cases examined included: class I/II (n = 3, 2%), class III/IV (n = 119, 78.8%), class V (n = 23, 15.2%), and class VI (n = 6, 4.0%). The mean serum creatinine level was 1.4 mg/dl. Tubulointerstitial lesions were recorded in 120 (79.5%) patients. Prior to receiving renal biopsy, 9 (6.0%) patients developed ESKD. During the follow-up period (mean, 58 months), an additional 47 patients (31.1%) progressed to ESKD. Multivariate analyses identified serum creatinine (hazard ratio [HR]: 1.7, 95% confidence interval [CI]: 1.42-2.03, p < 0.001) and IF (HR: 3.2, 95% CI: 1.58-6.49, p = 0.001) as independent risk factors of ESKD. Kaplan-Meier analysis further confirmed a heightened risk of ESKD associated with IF. CONCLUSION: Tubulointerstitial involvement is commonly observed in histopathological presentation of LN. However, IF, rather than II, or TA, was found to increase the risk of ESKD in our cohort. Therefore, to predict renal outcome in LN patients prior to adjusting immunosuppressive treatment, degree of IF should be reviewed.

UHRF1P contributes to IL-17A-mediated systemic lupus erythematosus via UHRF1-MAP4K3 axis.

Inflammatory T cells contribute to the pathogenesis of autoimmune diseases such as systemic lupus erythematosus (SLE). Analysis of the T-cell transcriptomics data of two independent SLE patient cohorts by three machine learning models revealed the pseudogene UHRF1P as a novel SLE biomarker. The pseudogene-encoded UHRF1P protein was overexpressed in peripheral blood T cells of SLE patients. The UHRF1P protein lacks the amino-terminus of its parental UHRF1 protein, resulting in missing the proteasome-binding ubiquitin-like (Ubl) domain of UHRF1. T-cell-specific UHRF1P transgenic mice manifested the induction of IL-17A and autoimmune inflammation. Mechanistically, UHFR1P prevented UHRF1-induced Lys48-linked ubiquitination and degradation of MAP4K3 (GLK), which is a kinase known to induce IL-17A. Consistently, IL-17A induction and autoimmune phenotypes of UHRF1P transgenic mice were obliterated by MAP4K3 knockout. Collectively, UHRF1P overexpression in T cells inhibits the E3 ligase function of its parental UHRF1 and induces autoimmune diseases.

Increased risk of malignancy in HLA-B27-positive patients with ankylosing spondylitis requiring biologics for sustained inflammation: A long-term, single-center retrospective study.

OBJECTIVES: To assess the link between the administration of biologic disease-modifying antirheumatic drugs (bDMARDs) and the risk of malignancy in human leukocyte antigen B27 (HLA-B27)-positive patients with ankylosing spondylitis (AS) experiencing sustained inflammation. METHODS: Between 2006 and 2021, 1445 HLA-B27-positive patients with AS were retrospectively evaluated. Among them, 112 patients required bDMARD therapy. The study compared conventional therapy with bDMARDs and investigated the risk factors for developing malignancies. RESULTS: During 8253 patient-years of follow-up, 38 (2.6%) patients developed various malignancies, including lung, liver, breast, and colon cancer. The risk of malignancy was significantly higher in the bDMARD-treated group compared to PS-matched groups receiving conventional synthetic DMARDs (csDMARD) and non-steroidal anti-inflammatory drugs. The cumulative risk of malignancies increased significantly after 6 years of follow-up. All patients who developed malignancy after bDMARD therapy received tumor necrosis factor-α inhibitors. Requiring bDMARD therapy, requiring bDMARDs in combination with csDMARD therapy, and being diagnosed with AS after 30 years of age were independent risk factors for developing malignancy. CONCLUSIONS: HLA-B27-positive AS patients with sustained inflammation requiring biologic therapy, particularly if diagnosed after age 30, may have an increased risk of malignancy. Regular cancer screenings are advisable for these patients while undergoing biologic treatment.

The Cross-Regulation Between Set1, Clr4, and Lsd1/2 in Schizosaccharomyces pombe.

Eukaryotic chromatin is organized into either silenced heterochromatin or relaxed euchromatin regions, which controls the accessibility of transcriptional machinery and thus regulates gene expression. In fission yeast, Schizosaccharomyces pombe, Set1 is the sole H3K4 methyltransferase and is mainly enriched at the promoters of actively transcribed genes. In contrast, Clr4 methyltransferase initiates H3K9 methylation, which has long been regarded as a hallmark of heterochromatic silencing. Lsd1 and Lsd2 are two highly conserved H3K4 and H3K9 demethylases. As these histone-modifying enzymes perform critical roles in maintaining histone methylation patterns and, consequently, gene expression profiles, cross-regulations among these enzymes are part of the complex regulatory networks. Thus, elucidating the mechanisms that govern their signaling and mutual regulations remains crucial. Here, we demonstrated that C-terminal truncation mutants, lsd1-ΔHMG and lsd2-ΔC, do not compromise the integrity of the Lsd1/2 complex but impair their chromatin-binding capacity at the promoter region of target genomic loci. We identified protein-protein interactions between Lsd1/2 and Raf2 or Swd2, which are the subunits of the Clr4 complex (CLRC) and Set1-associated complex (COMPASS), respectively. We showed that Clr4 and Set1 modulate the protein levels of Lsd1 and Lsd2 in opposite ways through the ubiquitin-proteasome-dependent pathway. During heat stress, the protein levels of Lsd1 and Lsd2 are upregulated in a Set1-dependent manner. The increase in protein levels is crucial for differential gene expression under stress conditions. Together, our results support a cross-regulatory model by which Set1 and Clr4 methyltransferases control the protein levels of Lsd1/2 demethylases to shape the dynamic chromatin landscape.

Long Non-Coding RNA Mir17hg Positively Regulates Melanogenesis by Inhibiting TGFß Receptor 2 under Psychological Stress.

Vitiligo is a common skin depigmentation disorder characterized by the patchy loss of skin color. Nowadays, it is recognized as being correlated with multiple genetic factors as well as the psychological conditions of individuals. Long noncoding RNAs have been reported to underlie the pathogenesis of vitiligo; however, the role of long noncoding RNAs in the stress-related depigmentation process remains largely unknown. In this study, the inhibition of melanocyte function was observed in C57BL/6J mice modeled through chronic restraint stress. Furthermore, downregulation of the expression of the long noncoding RNAs Mir17hg was identified using RNA sequencing. The regulatory role of Mir17hg in melanogenesis was also investigated in melanocytes and zebrafish embryos through overexpression or knockdown. Finally, TGFß receptor 2 was shown to be a downstream target in Mir17hg-mediated melanogenesis regulation, in which the classical TGFß/SMAD signaling cascade and the PI3K/AKT/mTOR signaling cascade play important roles. In conclusion, our results revealed an important regulatory role of Mir17hg in melanogenesis through inhibition of TGFßR2, which can provide a potential therapeutic target for treating skin depigmentation disorders.

Risk Factors and Incidence of Serious Infections in Patients With Systemic Lupus Erythematosus Undergoing Rituximab Therapy.

OBJECTIVE: To evaluate the risk and protective factors of serious infection (SI) in patients with systemic lupus erythematosus (SLE) within 180 days of rituximab (RTX) treatment. METHODS: Patients with SLE treated with RTX were analyzed. SI was defined as any infectious disease requiring hospitalization. The clinical characteristics, laboratory profiles, medications, and incidence rate (IR) are presented. Multivariate Cox proportional hazards models and Kaplan-Meier analysis for risk factors of SI were performed. RESULTS: A total of 174 patients with SLE receiving RTX treatment were enrolled. The overall IR of SIs was 51.0/100 patient-years (PYs). Pneumonia (30.4/100 PYs), followed by soft tissue infections, intra-abdominal infections, and Pneumocystis jiroveci pneumonia (all 6.1/100 PYs) were the leading types of SIs. Twelve patients died during the 180-day follow-up (crude mortality rate: 14.6/100 PYs). Chronic kidney disease (CKD), defined as an estimated glomerular filtration rate < 60 mL/min/1.73 m2 (hazard ratio [HR] 2.88, 95% CI 1.30-6.38), and a background prednisolone (PSL) equivalent dosage ≥ 15 mg/day (HR 3.50, 95% CI 1.57-7.78) were risk factors for SIs among all patients with SLE. Kaplan-Meier analysis confirmed the risk of SI for patients with SLE with CKD and a background PSL equivalent dosage ≥ 15 mg/day (log-rank P = 0.001 and 0.02, respectively). Hydroxychloroquine (HCQ) reduced the risk of SIs in patients with SLE (HR 0.35, 95% CI 0.15-0.82; log-rank P = 0.003). CONCLUSION: SI was prevalent in patients with SLE after RTX treatment. Patients with SLE with CKD and high-dose glucocorticoid use required constant vigilance. HCQ may reduce the risk of SI among patients with SLE administered RTX.

Pathology steered stratification network for subtype identification in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by three neurobiological factors beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for AD at a late stage, urging for early detection and prevention. However, existing statistical inference approaches in neuroimaging studies of AD subtype identification do not take into account the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles. PURPOSE: Integrating systems biology modeling with machine learning, the study aims to assist clinical AD prognosis by providing a subpopulation classification in accordance with essential biological principles, neurological patterns, and cognitive symptoms. METHODS: We propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along the brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term evolution trajectories that capture individual characteristic progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations. RESULTS: Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome. CONCLUSIONS: The proposed PSSN (i) reduces neuroimage data to low-dimensional feature vectors, (ii) combines AT[N]-Net based on real pathological pathways, (iii) predicts long-term biomarker trajectories, and (iv) stratifies subjects into fine-grained subtypes with distinct neurological underpinnings. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases.

Immune-mediated diseases after vaccinations with AZD1222, BNT-162b2, &/or mRNA-1273: An observational investigation of 78 patients.

BACKGROUND: Immune-mediated diseases (IMDs) after nucleic acid-based vaccines have been sporadically reported since their introduction during the worldwide COVID-19 crisis. Confirming their cause-effect association remains challenging. We analysed the effects of AZD1222 (ChAdOx1 nCoV-19), BNT-162b2, and/or mRNA-1273 on the development &/or deterioration of IMDs in terms of the time of clinical onsets of IMDs after exposure to these vaccines. METHODS: We retrospectively reviewed 78 in-patients in Taipei Veterans General Hospital, who presented with IMDs within 120 days after receiving AZD1222, BNT-162b2, &/or mRNA-1273 vaccinations in Taiwan from May 2021 to April 2022. The duration from inoculation to development of IMD was analysed by two-tailed Kolmogorov-Smirnov (K-S) test for goodness of fit. RESULTS: The average time to new IMDs or flare-up of the diseases following vaccinations was 36 ± 26 days for all 91 events in these 78 patients. The onset time of IMDs after vaccinations was not haphazard as analysed by two-tailed K-S test for overall 91 events (40 new and 51 deteriorating episodes, p < 0.001). The IMDs presenting as non-connective tissue diseases (non-CTDs) have a shorter duration of incubation after vaccinations than those of CTDs (<14.7 days, 95 % confidence interval [CI], 3.0 to 26.4, p = 0.014). Furthermore, systemic vasculitis and type 2 inflammatory diseases were observed exclusively in those receiving AZD1222. CONCLUSION: AZD1222, BNT-162b2, or mRNA-1273 influence the activities of IMDs in ways yet to be explored. High index of suspicion to IMDs after nucleic acid-based vaccine inoculation against COVID-19 may be important for primary care physicians.

DUSP8 induces TGF-ß-stimulated IL-9 transcription and Th9-mediated allergic inflammation by promoting nuclear export of Pur-α.

Dual-specificity phosphatase 8 (DUSP8) is a MAPK phosphatase that dephosphorylates and inactivates the kinase JNK. DUSP8 is highly expressed in T cells; however, the in vivo role of DUSP8 in T cells remains unclear. Using T cell-specific Dusp8 conditional KO (T-Dusp8 cKO) mice, mass spectrometry analysis, ChIP-Seq, and immune analysis, we found that DUSP8 interacted with Pur-α, stimulated interleukin-9 (IL-9) gene expression, and promoted Th9 differentiation. Mechanistically, DUSP8 dephosphorylated the transcriptional repressor Pur-α upon TGF-ß signaling, leading to the nuclear export of Pur-α and subsequent IL-9 transcriptional activation. Furthermore, Il-9 mRNA levels were induced in Pur-α-deficient T cells. In addition, T-Dusp8-cKO mice displayed reduction of IL-9 and Th9-mediated immune responses in the allergic asthma model. Reduction of Il-9 mRNA levels in T cells and allergic responses of T-Dusp8-cKO mice was reversed by Pur-α knockout. Remarkably, DUSP8 protein levels and the DUSP8-Pur-α interaction were indeed increased in the cytoplasm of T cells from people with asthma and patients with atopic dermatitis. Collectively, DUSP8 induces TGF-ß-stimulated IL-9 transcription and Th9-induced allergic responses by inhibiting the nuclear translocation of the transcriptional repressor Pur-α. DUSP8 may be a T-cell biomarker and therapeutic target for asthma and atopic dermatitis.

Rituximab induction and reinduction in granulomatosis with polyangiitis and microscopic polyangiitis: A retrospective multicenter study in Taiwan.

OBJECTIVES: This study aimed to investigate the clinical outcomes of granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) under rituximab induction and reinduction therapy in Taiwan. METHODS: We performed a retrospective study in patients with GPA or MPA receiving rituximab therapy from August 2008 to July 2020 in seven medical centers in Taiwan. The clinical characteristics and outcomes of these patients were analyzed. RESULTS: In total, 53 patients (18 with GPA and 35 with MPA) were included. Kidney involvement (82.9% vs. 22.2%, p < .001) and initial creatinine (3.25 ± 2.37 vs. 1.07 ± 0.82, p < .001) were significantly higher in MPA. Within 24 weeks after the first course of rituximab, there were seven deaths (five due to infection and two due to active disease) in patients with MPA (7/35, 20%) compared to 0 in patients with GPA. Of 33 patients receiving rituximab for kidney involvement, 23 survived and were free from renal replacement therapy at 24 weeks. Their chronic kidney disease (CKD) stages improved in 2 but progressed in 7, while 24 had stable CKD stages. Death or end-stage renal disease (ESRD) was associated with infection and higher initial creatinine. Reinduction therapy for relapse was required in 18 (39.1%) of 46 survivors, which was associated with anti-proteinase 3 (PR3) positive (odds ratio 3.667, p = .049) and younger age with a cutoff of 49.4 (AUC = 0.679, p = .030, sensitivity = 66.67%, specificity = 75%). CONCLUSION: Significant mortality occurred after rituximab induction, especially in patients with MPA. In survivors, age younger than 50 and anti-PR3 positive were associated with the risk of relapse requiring reinduction.

Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer's Disease.

BACKGROUND: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-ß (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. OBJECTIVE: To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology. METHODS: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. RESULTS: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. CONCLUSIONS: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-ß and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.

Elevated serum levels of T-cell immunoglobulin and mucin-domain containing molecule 3 in patients with systemic inflammation following COVID-19 vaccination.

BACKGROUND: ChAdOx1 nCoV-19 vaccine has been widely used. Some unexpected adverse effects such as the development of systemic hyper inflammation with multiorgan involvement after vaccination, in rare cases, have been reported. However, its pathogenesis remains unclear. METHODS: This study recruited two cases who suffered from systemic inflammation following ChAdOx1 nCoV-19 vaccine and two 30-year-old male volunteers without underlying disease who have received ChAdOx1 nCoV-19 vaccine as control group. Blood samples were collected from our patients and healthy subjects before and after treatment with anti-inflammatory agent such as glucocorticoid and tocilizumab. The immune profile from our patients and healthy controls were measured using a human XL cytokine Proteome Profiler array (ARY022b, R&D Systems). RESULTS: Biochemical parameters revealed leukocytosis with segmented neutrophil dominance and elevated serum levels of C-reactive protein (CRP), erythrocyte sedimentation rate, and ferritin in these two patients. The cytokine array revealed that mean levels of T cell immunoglobulin and mucin-domain containing-3 (TIM-3) (3640.3 vs 1580.5 pixels per inch [ppi]), B-cell activating factor (BAFF) (3036.8 vs 1471.0 ppi), urokinase plasminogen activator surface receptor (uPAR) (1043.1 vs 516.8 ppi), Resistin (1783.7 vs 711.3 ppi), platelet-derived growth factor (PDGF)-AB/BB (1980.7 vs 939.7 ppi), macrophage inflammatory protein-3-beta (MIP-3ß) (911.9 vs 346.2 ppi), and interferon-inducible T-cell alpha chemoattractant (I-TAC) (1026.3 vs 419.7 ppi) were 2-fold higher in the patients than in normal subjects who received ChAdOx1 nCoV-19 vaccine. CONCLUSION: We demonstrated that systemic inflammation may occur in subjects who have received the ChAdOx1 nCoV-19 vaccination. Moreover, we proposed immune markers, which may be implicated in the pathogenesis of systemic inflammation following COVID-19 vaccination as potential diagnostic biomarkers.

scENT for Revealing Gene Clusters From Single-Cell RNA-Seq Data.

Recently, the fast development of single-cell RNA-seq (scRNA-seq) techniques has enabled high-resolution transcriptomic statistical analysis of individual cells in heterogeneous tissues, which can help researchers to explore the relationship between genes and human diseases. The emerging scRNA-seq data results in new analysis methods aiming to identify cell-level clustering and annotations. However, there are few methods developed to gain insights into the gene-level clusters with biological significance. This study proposes a new deep learning-based framework, scENT (single cell gENe clusTer), to identify significant gene clusters from single-cell RNA-seq data. We started with clustering the scRNA-seq data into multiple optimal groups, followed by a gene set enrichment analysis to identify classes of over-represented genes. Considering high-dimensional data with extensive zeros and dropout issues, scENT integrates perturbation in the learning process of clustering scRNA-seq data to improve its robustness and performance. Experimental results show that scENT outperformed other benchmarking methods on simulation data. To validate the biological insights of scENT, we applied it to the public experimental scRNA-seq data profiled from patients with Alzheimer's disease and brain metastasis. scENT successfully identified novel functional gene clusters and associated functions, facilitating the discovery of prospective mechanisms and the understanding of related diseases.

Dual-specificity phosphatases 22-deficient T cells contribute to the pathogenesis of ankylosing spondylitis.

BACKGROUND: Dual-specificity phosphatases (DUSPs) can dephosphorylate both tyrosine and serine/threonine residues of their substrates and regulate T cell-mediated immunity and autoimmunity. The aim of this study was to investigate the potential roles of DUSPs in ankylosing spondylitis (AS). METHODS: Sixty AS patients and 45 healthy controls were enrolled in this study. Associations of gene expression of 23 DUSPs in peripheral T cells with inflammatory cytokine gene expression and disease activity of AS were analyzed. Finally, we investigated whether the characteristics of AS are developed in DUSP-knockout mice. RESULTS: The mRNA levels of DUSP4, DUSP5, DUSP6, DUSP7, and DUSP14 in peripheral T cells were significantly higher in AS group than those of healthy controls (all p < 0.05), while DUSP22 (also named JKAP) mRNA levels were significantly lower in AS group than healthy controls (p < 0.001). The mRNA levels of DUSP4, DUSP5, DUSP6, DUSP7, and DUSP14 in T cells were positively correlated with mRNA levels of tumor necrosis factor-α (TNF-α), whereas DUSP22 was inversely correlated (all p < 0.05). In addition, inverse correlations of DUSP22 gene expression in peripheral T cells with C-reactive protein, erythrocyte sedimentation rate, and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) were observed (all p < 0.05). More importantly, aged DUSP22 knockout mice spontaneously developed syndesmophyte formation, which was accompanied by an increase of TNF-α+, interleukin-17A+, and interferon-γ+ CD3+ T cells. CONCLUSIONS: DUSP22 may play a crucial role in the pathogenesis and regulation of disease activity of AS.

NLRP12 is an innate immune checkpoint for repressing IFN signatures and attenuating lupus nephritis progression.

Signaling driven by nucleic acid sensors participates in interferonopathy-mediated autoimmune diseases. NLRP12, a pyrin-containing NLR protein, is a negative regulator of innate immune activation and type I interferon (IFN-I) production. Peripheral blood mononuclear cells (PBMCs) derived from systemic lupus erythematosus (SLE) patients expressed lower levels of NLRP12, with an inverse correlation with IFNA expression and high disease activity. NLRP12 expression was transcriptionally suppressed by runt-related transcription factor 1-dependent (RUNX1-dependent) epigenetic regulation under IFN-I treatment, which enhanced a negative feedback loop between low NLRP12 expression and IFN-I production. Reduced NLRP12 protein levels in SLE monocytes was linked to spontaneous activation of innate immune signaling and hyperresponsiveness to nucleic acid stimulations. Pristane-treated Nlrp12-/- mice exhibited augmented inflammation and immune responses; and substantial lymphoid hypertrophy was characterized in NLRP12-deficient lupus-prone mice. NLRP12 deficiency mediated the increase of autoantibody production, intensive glomerular IgG deposition, monocyte recruitment, and the deterioration of kidney function. These were bound in an IFN-I signature-dependent manner in the mouse models. Collectively, we reveal a remarkable link between low NLRP12 expression and lupus progression, which suggests the impact of NLRP12 on homeostasis and immune resilience.

Dual-Stream Subspace Clustering Network for revealing gene targets in Alzheimer's disease.

The rapid development of scRNA-seq technology in recent years has enabled us to capture high-throughput gene expression profiles at single-cell resolution, reveal the heterogeneity of complex cell populations, and greatly advance our understanding of the underlying mechanisms in human diseases. Traditional methods for gene co-expression clustering are limited to discovering effective gene groups in scRNA-seq data. In this paper, we propose a novel gene clustering method based on convolutional neural networks called Dual-Stream Subspace Clustering Network (DS-SCNet). DS-SCNet can accurately identify important gene clusters from large scales of single-cell RNA-seq data and provide useful information for downstream analysis. Based on the simulated datasets, DS-SCNet successfully clusters genes into different groups and outperforms mainstream gene clustering methods, such as DBSCAN and DESC, across different evaluation metrics. To explore the biological insights of our proposed method, we applied it to real scRNA-seq data of patients with Alzheimer's disease (AD). DS-SCNet analyzed the single-cell RNA-seq data with 10,850 genes, and accurately identified 8 optimal clusters from 6673 cells. Enrichment analysis of these gene clusters revealed functional signaling pathways including the ILS signaling, the Rho GTPase signaling, and hemostasis pathways. Further analysis of gene regulatory networks identified new hub genes such as ELF4 as important regulators of AD, which indicates that DS-SCNet contributes to the discovery and understanding of the pathogenesis in Alzheimer's disease.

Risk factors for mortality in systemic lupus erythematosus patients: Analysis of adult and pediatric cohorts in Taiwan.

BACKGROUND: Overall survival of systemic lupus erythematosus (SLE) patients significantly increased in recent decades, however, the relative risk of mortality is still high. Long-term survival outcome of pediatric SLE remains unclear. This study aims to explore the long-term survival rate and its predictors in patients with systemic lupus erythematosus (SLE). METHODS: A retrospective, hospital-based cohort study was performed between 2004 and 2018 in a tertiary referral medical center in Taiwan. Data on comorbidities, medications, and causes of admission were collected for risk factor analysis using time-dependent multivariate Cox proportional hazards models. RESULTS: A total of 2392 adults and 115 pediatric SLE patients were enrolled (female, n = 2157 and 95, respectively). The 10-year survival rates were 93.2%, 90.2%, 98.9%, and 100% in adult women, adult men, girls, and boys with SLE, respectively. The overall mortality rate was 2.09 case/100 patient-years (PY) for male SLE and 1.39 case/100 PY for female SLE patients. Male SLE patients did not have a statistically significantly higher mortality rate than female SLE patients in each age stratification. Infectious disease (n = 119), heart failure (n = 21), and cerebrovascular accident (n = 14) were the leading causes of death in adult SLE patients. Advanced age (hazard ratio [HR]: 1.04, 95% confidence interval [CI]: 1.03-1.05), treatment with mean dosage of systemic glucocorticoid equivalent to >10 mg/d of prednisolone (HR: 1.71, 95% CI: 1.14-2.57), comorbidities with malignancy (HR: 1.94, 95% CI: 1.22-3.09), chronic kidney disease (HR: 1.86, 95% CI: 1.25-2.77), hypertension (HR: 1.42, 95% CI: 1.01-1.98), and admission due to bacterial pneumonia (HR: 1.92, 95% CI: 1.12-3.31) and sepsis (HR: 2.78, 95% CI: 1.51-5.13) were independent risk factors for mortality in SLE patients. CONCLUSION: SLE patients with advanced age, malignancy, chronic kidney disease, hypertension, treated with a higher average dosage of glucocorticoids, and admission due to bacterial pneumonia and sepsis have an increased risk of mortality.

Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data.

Lung cancer is one of the leading causes of cancer-related death, with a five-year survival rate of 18%. It is a priority for us to understand the underlying mechanisms affecting lung cancer therapeutics' implementation and effectiveness. In this study, we combine the power of Bioinformatics and Systems Biology to comprehensively uncover functional and signaling pathways of drug treatment using bioinformatics inference and multiscale modeling of both scRNA-seq data and proteomics data. Based on a time series of lung adenocarcinoma derived A549 cells after DEX treatment, we first identified the differentially expressed genes (DEGs) in those lung cancer cells. Through the interrogation of regulatory network of those DEGs, we identified key hub genes including TGFß, MYC, and SMAD3 varied underlie DEX treatment. Further gene set enrichment analysis revealed the TGFß signaling pathway as the top enriched term. Those genes involved in the TGFß pathway and their crosstalk with the ERBB pathway presented a strong survival prognosis in clinical lung cancer samples. With the basis of biological validation and literature-based curation, a multiscale model of tumor regulation centered on both TGFß-induced and ERBB-amplified signaling pathways was developed to characterize the dynamic effects of DEX therapy on lung cancer cells. Our simulation results were well matched to available data of SMAD2, FOXO3, TGFß1, and TGFßR1 over the time course. Moreover, we provided predictions of different doses to illustrate the trend and therapeutic potential of DEX treatment. The innovative and cross-disciplinary approach can be further applied to other computational studies in tumorigenesis and oncotherapy. We released the approach as a user-friendly tool named BIMM (Bioinformatic Inference and Multiscale Modeling), with all the key features available at https://github.com/chenm19/BIMM.