Crosstalk between CD64+MHCII+ macrophages and CD4+ T cells drives joint pathology during chikungunya.

Communications between immune cells are essential to ensure appropriate coordination of their activities. Here, we observed the infiltration of activated macrophages into the joint-footpads of chikungunya virus (CHIKV)-infected animals. Large numbers of CD64+MHCII+ and CD64+MHCII- macrophages were present in the joint-footpad, preceded by the recruitment of their CD11b+Ly6C+ inflammatory monocyte precursors. Recruitment and differentiation of these myeloid subsets were dependent on CD4+ T cells and GM-CSF. Transcriptomic and gene ontology analyses of CD64+MHCII+ and CD64+MHCII- macrophages revealed 89 differentially expressed genes, including genes involved in T cell proliferation and differentiation pathways. Depletion of phagocytes, including CD64+MHCII+ macrophages, from CHIKV-infected mice reduced disease pathology, demonstrating that these cells play a pro-inflammatory role in CHIKV infection. Together, these results highlight the synergistic dynamics of immune cell crosstalk in driving CHIKV immunopathogenesis. This study provides new insights in the disease mechanism and offers opportunities for development of novel anti-CHIKV therapeutics.

Elucidating salient site-specific functional connectivity features and site-invariant biomarkers in schizophrenia via deep neural networks.

Schizophrenia is a highly heterogeneous disorder and salient functional connectivity (FC) features have been observed to vary across study sites, warranting the need for methods that can differentiate between site-invariant FC biomarkers and site-specific salient FC features. We propose a technique named Semi-supervised learning with data HaRmonisation via Encoder-Decoder-classifier (SHRED) to examine these features from resting state functional magnetic resonance imaging scans gathered from four sites. Our approach involves an encoder-decoder-classifier architecture that simultaneously performs data harmonisation and semi-supervised learning (SSL) to deal with site differences and labelling inconsistencies across sites respectively. The minimisation of reconstruction loss from SSL was shown to improve model performance even within small datasets whilst data harmonisation often led to lower model generalisability, which was unaffected using the SHRED technique. We show that our proposed model produces site-invariant biomarkers, most notably the connection between transverse temporal gyrus and paracentral lobule. Site-specific salient FC features were also elucidated, especially implicating the paracentral lobule for our local dataset. Our examination of these salient FC features demonstrates how site-specific features and site-invariant biomarkers can be differentiated, which can deepen our understanding of the neurobiology of schizophrenia.

Multi-modal graph neural network for early diagnosis of Alzheimer's disease from sMRI and PET scans.

In recent years, deep learning models have been applied to neuroimaging data for early diagnosis of Alzheimer's disease (AD). Structural magnetic resonance imaging (sMRI) and positron emission tomography (PET) images provide structural and functional information about the brain, respectively. Combining these features leads to improved performance than using a single modality alone in building predictive models for AD diagnosis. However, current multi-modal approaches in deep learning, based on sMRI and PET, are mostly limited to convolutional neural networks, which do not facilitate integration of both image and phenotypic information of subjects. We propose to use graph neural networks (GNN) that are designed to deal with problems in non-Euclidean domains. In this study, we demonstrate how brain networks are created from sMRI or PET images and can be used in a population graph framework that combines phenotypic information with imaging features of the brain networks. Then, we present a multi-modal GNN framework where each modality has its own branch of GNN and a technique that combines the multi-modal data at both the level of node vectors and adjacency matrices. Finally, we perform late fusion to combine the preliminary decisions made in each branch and produce a final prediction. As multi-modality data becomes available, multi-source and multi-modal is the trend of AD diagnosis. We conducted explorative experiments based on multi-modal imaging data combined with non-imaging phenotypic information for AD diagnosis and analyzed the impact of phenotypic information on diagnostic performance. Results from experiments demonstrated that our proposed multi-modal approach improves performance for AD diagnosis. Our study also provides technical reference and support the need for multivariate multi-modal diagnosis methods.

Prolonged inflammation in patients hospitalized for coronavirus disease 2019 (COVID-19) resolves 2 years after infection.

Long-term complications from coronavirus disease 2019 (COVID-19) are concerning, as survivors can develop subclinical multiorgan dysfunction. It is unknown if such complications are due to prolonged inflammation, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination may reduce sequela. We conducted a prospective longitudinal study on hospitalized patients over 24 months. Clinical symptoms were collected by self-reporting during follow-up, along with blood samples for quantification of inflammatory markers and immune cell frequencies. All patients were given one dose of mRNA vaccine at 12-16 months. Their immune profiles at 12 and 24 months were compared. Approximately 37% and 39% of our patients reported post-COVID-19 symptoms at 12 and 24 months, respectively. The proportion of symptomatic patients with more than one symptom decreased from 69% at 12 months to 56% at 24 months. Longitudinal cytokine profiling revealed a cluster of individuals with persistently high inflammatory cytokine levels 12 months after infection. Patients with prolonged inflammation showed elevated terminally differentiated memory T cells in their blood; 54% had symptoms at 12 months. The majority of inflammatory markers and dysregulated immune cells in vaccinated patients recovered to a healthy baseline at 24 months, even though symptoms persisted. Post-COVID-19 symptoms can linger for 2 years after the initial infection and are associated with prolonged inflammation. Prolonged inflammation in hospitalized patients resolves after 2 years. We define a set of analytes associated with persistent inflammation and presence of symptoms, which could be useful biomarkers for identifying and monitoring high-risk survivors.

Encephalitis and poor neuronal death-mediated control of herpes simplex virus in human inherited RIPK3 deficiency.

Inborn errors of TLR3-dependent type I IFN immunity in cortical neurons underlie forebrain herpes simplex virus-1 (HSV-1) encephalitis (HSE) due to uncontrolled viral growth and subsequent cell death. We report an otherwise healthy patient with HSE who was compound heterozygous for nonsense (R422*) and frameshift (P493fs9*) RIPK3 variants. Receptor-interacting protein kinase 3 (RIPK3) is a ubiquitous cytoplasmic kinase regulating cell death outcomes, including apoptosis and necroptosis. In vitro, the R422* and P493fs9* RIPK3 proteins impaired cellular apoptosis and necroptosis upon TLR3, TLR4, or TNFR1 stimulation and ZBP1/DAI-mediated necroptotic cell death after HSV-1 infection. The patient's fibroblasts displayed no detectable RIPK3 expression. After TNFR1 or TLR3 stimulation, the patient's cells did not undergo apoptosis or necroptosis. After HSV-1 infection, the cells supported excessive viral growth despite normal induction of antiviral IFN-ß and IFN-stimulated genes (ISGs). This phenotype was, nevertheless, rescued by application of exogenous type I IFN. The patient's human pluripotent stem cell (hPSC)-derived cortical neurons displayed impaired cell death and enhanced viral growth after HSV-1 infection, as did isogenic RIPK3-knockout hPSC-derived cortical neurons. Inherited RIPK3 deficiency therefore confers a predisposition to HSE by impairing the cell death-dependent control of HSV-1 in cortical neurons but not their production of or response to type I IFNs.

Human IRF1 governs macrophagic IFN-γ immunity to mycobacteria.

Inborn errors of human IFN-γ-dependent macrophagic immunity underlie mycobacterial diseases, whereas inborn errors of IFN-α/ß-dependent intrinsic immunity underlie viral diseases. Both types of IFNs induce the transcription factor IRF1. We describe unrelated children with inherited complete IRF1 deficiency and early-onset, multiple, life-threatening diseases caused by weakly virulent mycobacteria and related intramacrophagic pathogens. These children have no history of severe viral disease, despite exposure to many viruses, including SARS-CoV-2, which is life-threatening in individuals with impaired IFN-α/ß immunity. In leukocytes or fibroblasts stimulated in vitro, IRF1-dependent responses to IFN-γ are, both quantitatively and qualitatively, much stronger than those to IFN-α/ß. Moreover, IRF1-deficient mononuclear phagocytes do not control mycobacteria and related pathogens normally when stimulated with IFN-γ. By contrast, IFN-α/ß-dependent intrinsic immunity to nine viruses, including SARS-CoV-2, is almost normal in IRF1-deficient fibroblasts. Human IRF1 is essential for IFN-γ-dependent macrophagic immunity to mycobacteria, but largely redundant for IFN-α/ß-dependent antiviral immunity.

Inborn errors of OAS-RNase L in SARS-CoV-2-related multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic double-stranded RNA (dsRNA)-sensing OAS1 and OAS2 generate 2'-5'-linked oligoadenylates (2-5A) that activate the single-stranded RNA-degrading ribonuclease L (RNase L). Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNase L deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-deficient but not RNase L-deficient cells. Cytokine production in RNase L-deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Recessive OAS-RNase L deficiencies in these patients unleash the production of SARS-CoV-2-triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C.

Lower vaccine-acquired immunity in the elderly population following two-dose BNT162b2 vaccination is alleviated by a third vaccine dose.

Understanding the impact of age on vaccinations is essential for the design and delivery of vaccines against SARS-CoV-2. Here, we present findings from a comprehensive analysis of multiple compartments of the memory immune response in 312 individuals vaccinated with the BNT162b2 SARS-CoV-2 mRNA vaccine. Two vaccine doses induce high antibody and T cell responses in most individuals. However, antibody recognition of the Spike protein of the Delta and Omicron variants is less efficient than that of the ancestral Wuhan strain. Age-stratified analyses identify a group of low antibody responders where individuals ≥60 years are overrepresented. Waning of the antibody and cellular responses is observed in 30% of the vaccinees after 6 months. However, age does not influence the waning of these responses. Taken together, while individuals ≥60 years old take longer to acquire vaccine-induced immunity, they develop more sustained acquired immunity at 6 months post-vaccination. A third dose strongly boosts the low antibody responses in the older individuals against the ancestral Wuhan strain, Delta and Omicron variants.

Combining Neuroimaging and Omics Datasets for Disease Classification Using Graph Neural Networks.

Both neuroimaging and genomics datasets are often gathered for the detection of neurodegenerative diseases. Huge dimensionalities of neuroimaging data as well as omics data pose tremendous challenge for methods integrating multiple modalities. There are few existing solutions that can combine both multi-modal imaging and multi-omics datasets to derive neurological insights. We propose a deep neural network architecture that combines both structural and functional connectome data with multi-omics data for disease classification. A graph convolution layer is used to model functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data simultaneously to learn compact representations of the connectome. A separate set of graph convolution layers are then used to model multi-omics datasets, expressed in the form of population graphs, and combine them with latent representations of the connectome. An attention mechanism is used to fuse these outputs and provide insights on which omics data contributed most to the model's classification decision. We demonstrate our methods for Parkinson's disease (PD) classification by using datasets from the Parkinson's Progression Markers Initiative (PPMI). PD has been shown to be associated with changes in the human connectome and it is also known to be influenced by genetic factors. We combine DTI and fMRI data with multi-omics data from RNA Expression, Single Nucleotide Polymorphism (SNP), DNA Methylation and non-coding RNA experiments. A Matthew Correlation Coefficient of greater than 0.8 over many combinations of multi-modal imaging data and multi-omics data was achieved with our proposed architecture. To address the paucity of paired multi-modal imaging data and the problem of imbalanced data in the PPMI dataset, we compared the use of oversampling against using CycleGAN on structural and functional connectomes to generate missing imaging modalities. Furthermore, we performed ablation studies that offer insights into the importance of each imaging and omics modality for the prediction of PD. Analysis of the generated attention matrices revealed that DNA Methylation and SNP data were the most important omics modalities out of all the omics datasets considered. Our work motivates further research into imaging genetics and the creation of more multi-modal imaging and multi-omics datasets to study PD and other complex neurodegenerative diseases.

Decreased memory B cell frequencies in COVID-19 delta variant vaccine breakthrough infection.

The SARS-CoV-2 Delta (B.1.617.2) variant is capable of infecting vaccinated persons. An open question remains as to whether deficiencies in specific vaccine-elicited immune responses result in susceptibility to vaccine breakthrough infection. We investigated 55 vaccine breakthrough infection cases (mostly Delta) in Singapore, comparing them against 86 vaccinated close contacts who did not contract infection. Vaccine breakthrough cases showed lower memory B cell frequencies against SARS-CoV-2 receptor-binding domain (RBD). Compared to plasma antibodies, antibodies secreted by memory B cells retained a higher fraction of neutralizing properties against the Delta variant. Inflammatory cytokines including IL-1ß and TNF were lower in vaccine breakthrough infections than primary infection of similar disease severity, underscoring the usefulness of vaccination in preventing inflammation. This report highlights the importance of memory B cells against vaccine breakthrough and suggests that lower memory B cell levels may be a correlate of risk for Delta vaccine breakthrough infection.

Malaria abrogates O'nyong-nyong virus pathologies by restricting virus infection in nonimmune cells.

O'nyongnyong virus (ONNV) is a re-emerging alphavirus previously known to be transmitted by main malaria vectors, thus suggesting the possibility of coinfections with arboviruses in co-endemic areas. However, the pathological outcomes of such infections remain unknown. Using murine coinfection models, we demonstrated that a preexisting blood-stage Plasmodium infection suppresses ONNV-induced pathologies. We further showed that suppression of viremia and virus dissemination are dependent on Plasmodium-induced IFNγ and are associated with reduced infection of CD45- cells at the site of virus inoculation. We further proved that treatment with IFNγ or plasma samples from Plasmodium vivax-infected patients containing IFNγ are able to restrict ONNV infection in human fibroblast, synoviocyte, skeletal muscle, and endothelial cell lines. Mechanistically, the role of IFNγ in restricting ONNV infection was confirmed in in vitro infection assays through the generation of an IFNγ receptor 1 α chain (IFNγR1)-deficient cell line.

Robust Virus-Specific Adaptive Immunity in COVID-19 Patients with SARS-CoV-2 Δ382 Variant Infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that have become dominant as the pandemic progresses bear the ORF8 mutation together with multiple spike mutations. A 382-nucleotide deletion (Δ382) in the ORF7b and ORF8 regions has been associated with milder disease phenotype and less systemic inflammation in COVID-19 patients. However, its impact on host immunity against SARS-CoV-2 remains undefined. Here, RNA-sequencing was performed to elucidate whole blood transcriptomic profiles and identify contrasting immune signatures between patients infected with either wildtype or Δ382 SARS-CoV-2 variant. Interestingly, the immune landscape of Δ382 SARS-CoV-2 infected patients featured an increased adaptive immune response, evidenced by enrichment of genes related to T cell functionality, a more robust SARS-CoV-2-specific T cell immunity, as well as a more rapid antibody response. At the molecular level, eukaryotic initiation factor 2 signaling was found to be upregulated in patients bearing Δ382, and its associated genes were correlated with systemic levels of T cell-associated and pro-inflammatory cytokines. This study provides more in-depth insight into the host-pathogen interactions of ORF8 with great promise as a therapeutic target to combat SARS-CoV-2 infection.

Data-Driven Analysis of COVID-19 Reveals Persistent Immune Abnormalities in Convalescent Severe Individuals.

Severe SARS-CoV-2 infection can trigger uncontrolled innate and adaptive immune responses, which are commonly associated with lymphopenia and increased neutrophil counts. However, whether the immune abnormalities observed in mild to severely infected patients persist into convalescence remains unclear. Herein, comparisons were drawn between the immune responses of COVID-19 infected and convalescent adults. Strikingly, survivors of severe COVID-19 had decreased proportions of NKT and Vδ2 T cells, and increased proportions of low-density neutrophils, IgA+/CD86+/CD123+ non-classical monocytes and hyperactivated HLADR+CD38+ CD8+ T cells, and elevated levels of pro-inflammatory cytokines such as hepatocyte growth factor and vascular endothelial growth factor A, long after virus clearance. Our study suggests potential immune correlates of "long COVID-19", and defines key cells and cytokines that delineate true and quasi-convalescent states.

Differential Cytokine Responses in Hospitalized COVID-19 Patients Limit Efficacy of Remdesivir.

A significant proportion of COVID-19 patients will progress to critical illness requiring invasive mechanical ventilation. This accentuates the need for a therapy that can reduce the severity of COVID-19. Clinical trials have shown the effectiveness of remdesivir in shortening recovery time and decreasing progression to respiratory failure and mechanical ventilation. However, some studies have highlighted its lack of efficacy in patients on high-flow oxygen and mechanical ventilation. This study uncovers some underlying immune response differences between responders and non-responders to remdesivir treatment. Immunological analyses revealed an upregulation of tissue repair factors BDNF, PDGF-BB and PIGF-1, as well as an increase in ratio of Th2-associated cytokine IL-4 to Th1-associated cytokine IFN-γ. Serological profiling of IgG subclasses corroborated this observation, with significantly higher magnitude of increase in Th2-associated IgG2 and IgG4 responses. These findings help to identify the mechanisms of immune regulation accompanying successful remdesivir treatment in severe COVID-19 patients.

Persistent Symptoms and Association With Inflammatory Cytokine Signatures in Recovered Coronavirus Disease 2019 Patients.

BACKGROUND: The complications and sequelae of coronavirus disease 2019 (COVID-19) and their effect on long-term health are unclear, and the trajectory of associated immune dysregulation is poorly understood. METHODS: We conducted a prospective longitudinal multicenter cohort study at 4 public hospitals in Singapore. Patients with COVID-19 were monitored for a median of 6 months after recovery from acute infection. Clinical symptoms and radiologic data were collected, along with plasma samples for quantification of immune mediators. The relationship between clinical symptoms and immune cytokine profiles was investigated. RESULTS: Two hundred eighty-eight participants were recruited, and follow-up data were available for 183, 175, and 120 participants at days 30, 90, and 180 postsymptom onset, respectively. Symptoms related to COVID-19 were present in 31 (16.9%), 13 (7.4%), and 14 (11.7%) at days 30, 90, and 180. In a multivariable model, age >65 years, non-Chinese ethnicity, and the severity of acute infection were associated with increased likelihood of persistent symptoms. Recovered COVID-19 patients had elevated levels of proinflammatory interleukin (IL)-17A, stem cell factor, IL-12p70, and IL-1ß and pro-angiogenic macrophage inflammatory protein 1ß, brain-derived neurotrophic factor, and vascular endothelial growth factor at day 180 compared with healthy controls. Higher levels of monocyte chemoattractant protein-1 and platelet-derived growth factor-BB were detected in patients with persistent symptoms, versus symptom-free patients. CONCLUSIONS: Approximately 10% of recovered patients had persistent symptoms 6 months after initial infection. Immune cytokine signatures of the recovered patients reflected ongoing chronic inflammation and angiogenesis. Patients with COVID-19 should be monitored closely for emerging long-term health consequences.

Augmenting Product Defect Surveillance Through Web Crawling and Machine Learning in Singapore.

INTRODUCTION: Substandard medicines are medicines that fail to meet their quality standards and/or specifications. Substandard medicines can lead to serious safety issues affecting public health. With the increasing number of pharmaceuticals and the complexity of the pharmaceutical manufacturing supply chain, monitoring for substandard medicines via manual environmental scanning can be laborious and time consuming. METHODS: A web crawler was developed to automatically detect and extract alerts on substandard medicines published on the Internet by regulatory agencies. The crawled data were labelled as related to substandard medicines or not. An expert-derived keyword-based classification algorithm was compared against machine learning algorithms to identify substandard medicine alerts on two validation datasets (n = 4920 and n = 2458) from a later time period than training data. Models were comparatively assessed for recall, precision and their F1 scores (harmonic mean of precision and recall). RESULTS: The web crawler routinely extracted alerts from the 46 web pages belonging to nine regulatory agencies. From October 2019 to May 2020, 12,156 unique alerts were crawled of which 7378 (60.7%) alerts were set aside for validation and contained 1160 substandard medicine alerts (15.7%). An ensemble approach of combining machine learning and keywords achieved the best recall (94% and 97%), precision (85% and 80%) and F1 scores (89% and 88%) on temporal validation. CONCLUSIONS: Combining robust web crawler programmes with rigorously tested filtering algorithms based on machine learning and keyword models can automate and expand horizon scanning capabilities for issues relating to substandard medicines.

Asymptomatic COVID-19: disease tolerance with efficient anti-viral immunity against SARS-CoV-2.

The immune responses and mechanisms limiting symptom progression in asymptomatic cases of SARS-CoV-2 infection remain unclear. We comprehensively characterized transcriptomic profiles, cytokine responses, neutralization capacity of antibodies, and cellular immune phenotypes of asymptomatic patients with acute SARS-CoV-2 infection to identify potential protective mechanisms. Compared to symptomatic patients, asymptomatic patients had higher counts of mature neutrophils and lower proportion of CD169+ expressing monocytes in the peripheral blood. Systemic levels of pro-inflammatory cytokines were also lower in asymptomatic patients, accompanied by milder pro-inflammatory gene signatures. Mechanistically, a more robust systemic Th2 cell signature with a higher level of virus-specific Th17 cells and a weaker yet sufficient neutralizing antibody profile against SARS-CoV-2 was observed in asymptomatic patients. In addition, asymptomatic COVID-19 patients had higher systemic levels of growth factors that are associated with cellular repair. Together, the data suggest that asymptomatic patients mount less pro-inflammatory and more protective immune responses against SARS-CoV-2 indicative of disease tolerance. Insights from this study highlight key immune pathways that could serve as therapeutic targets to prevent disease progression in COVID-19.

Association of SARS-CoV-2 clades with clinical, inflammatory and virologic outcomes: An observational study.

BACKGROUND: Host determinants of severe coronavirus disease 2019 include advanced age, comorbidities and male sex. Virologic factors may also be important in determining clinical outcome and transmission rates, but limited patient-level data is available. METHODS: We conducted an observational cohort study at seven public hospitals in Singapore. Clinical and laboratory data were collected and compared between individuals infected with different SARS-CoV-2 clades. Firth's logistic regression was used to examine the association between SARS-CoV-2 clade and development of hypoxia, and quasi-Poisson regression to compare transmission rates. Plasma samples were tested for immune mediator levels and the kinetics of viral replication in cell culture were compared. FINDINGS: 319 patients with PCR-confirmed SARS-CoV-2 infection had clinical and virologic data available for analysis. 29 (9%) were infected with clade S, 90 (28%) with clade L/V, 96 (30%) with clade G (containing D614G variant), and 104 (33%) with other clades 'O' were assigned to lineage B.6. After adjusting for age and other covariates, infections with clade S (adjusted odds ratio (aOR) 0·030 (95% confidence intervals (CI): 0·0002-0·29)) or clade O (B·6) (aOR 0·26 (95% CI 0·064-0·93)) were associated with lower odds of developing hypoxia requiring supplemental oxygen compared with clade L/V. Patients infected with clade L/V had more pronounced systemic inflammation with higher concentrations of pro-inflammatory cytokines, chemokines and growth factors. No significant difference in the severity of clade G infections was observed (aOR 0·95 (95% CI: 0·35-2·52). Though viral loads were significantly higher, there was no evidence of increased transmissibility of clade G, and replicative fitness in cell culture was similar for all clades. INTERPRETATION: Infection with clades L/V was associated with increased severity and more systemic release of pro-inflammatory cytokines. Infection with clade G was not associated with changes in severity, and despite higher viral loads there was no evidence of increased transmissibility.