Immuno-informatics analysis predicts B and T cell consensus epitopes for designing peptide vaccine against SARS-CoV-2 with 99.82% global population coverage.

The current global pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has taken a substantial number of lives across the world. Although few vaccines have been rolled-out, a number of vaccine candidates are still under clinical trials at various pharmaceutical companies and laboratories around the world. Considering the intrinsic nature of viruses in mutating and evolving over time, persistent efforts are needed to develop better vaccine candidates. In this study, various immuno-informatics tools and bioinformatics databases were deployed to derive consensus B-cell and T-cell epitope sequences of SARS-CoV-2 spike glycoprotein. This approach has identified four potential epitopes which have the capability to initiate both antibody and cell-mediated immune responses, are non-allergenic and do not trigger autoimmunity. These peptide sequences were also evaluated to show 99.82% of global population coverage based on the genotypic frequencies of HLA binding alleles for both MHC class-I and class-II and are unique for SARS-CoV-2 isolated from human as a host species. Epitope number 2 alone had a global population coverage of 98.2%. Therefore, we further validated binding and interaction of its constituent T-cell epitopes with their corresponding HLA proteins using molecular docking and molecular dynamics simulation experiments, followed by binding free energy calculations with molecular mechanics Poisson-Boltzmann surface area, essential dynamics analysis and free energy landscape analysis. The immuno-informatics pipeline described and the candidate epitopes discovered herein could have significant impact upon efforts to develop globally effective SARS-CoV-2 vaccines.

Anti-inflammatory effects of phytocannabinoids and terpenes on inflamed Tregs and Th17 cells in vitro.

AIMS: Phytocannabinoids and terpenes from Cannabis sativa have demonstrated limited anti-inflammatory and analgesic effects in several inflammatory conditions. In the current study, we test the hypothesis that phytocannabinoids exert immunomodulatory effects in vitro by decreasing inflammatory cytokine expression and activation. KEY METHODS: CD3/CD28 and lipopolysaccharide activated peripheral blood mononuclear cells (PBMCs) from healthy donors (n = 6) were treated with phytocannabinoid compounds and terpenes in vitro. Flow cytometry was used to determine regulatory T cell (Treg) and T helper 17 (Th17) cell responses to treatments. Cell pellets were harvested for qRT-PCR gene expression analysis of cytokines, cell activation markers, and inflammation-related receptors. Cell culture supernatants were analysed by ELISA to quantify IL-6, TNF-α and IL-10 secretion. MAIN FINDINGS: In an initial screen of 20 µM cannabinoids and terpenes which were coded to blind investigators, cannabigerol (GL4a), caryophyllene oxide (GL5a) and gamma-terpinene (GL6a) significantly reduced cytotoxicity and gene expression levels of IL6, IL10, TNF, TRPV1, CNR1, HTR1A, FOXP3, RORC and NFKΒ1. Tetrahydrocannabinol (GL7a) suppression of T cell activation was associated with downregulation of RORC and NFKΒ1 gene expression and reduced IL-6 (p < 0.0001) and IL10 (p < 0.01) secretion. Cannabidiol (GL1b) significantly suppressed activation of Tregs (p < 0.05) and Th17 cells (p < 0.05) in a follow-on in vitro dose-response study. IL-6 (p < 0.01) and IL-10 (p < 0.01) secretion was significantly reduced with 50 µM cannabidiol. SIGNIFICANCE: The study provides the first evidence that cannabidiol and tetrahydrocannabinol suppress extracellular expression of both anti- and pro-inflammatory cytokines in an in vitro PBMC model of inflammation.

ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients.

Rheumatoid arthritis (RA) is a chronic autoimmune condition, characterised by joint pain, damage and disability, which can be addressed in a high proportion of patients by timely use of targeted biologic treatments. However, the patients, non-responsive to the treatments often suffer from refractoriness of the disease, leading to poor quality of life. Additionally, the biologic treatments are expensive. We obtained plasma samples from N = 144 participants with RA, who were about to commence anti-tumour necrosis factor (anti-TNF) therapy. These samples were sent to Olink Proteomics, Uppsala, Sweden, where proximity extension assays of 4 panels, containing 92 proteins each, were performed. A total of n = 89 samples of patients passed the quality control of anti-TNF treatment response data. The preliminary analysis of plasma protein expression values suggested that the RA population could be divided into two distinct molecular sub-groups (endotypes). However, these broad groups did not predict response to anti-TNF treatment, but were significantly different in terms of gender and their disease activity. We then labelled these patients as responders (n = 60) and non-responders (n = 29) based on the change in disease activity score (DAS) after 6 months of anti-TNF treatment and applied machine learning (ML) with a rigorous 5-fold nested cross-validation scheme to filter 17 proteins that were significantly associated with the treatment response. We have developed a ML based classifier ATRPred (anti-TNF treatment response predictor), which can predict anti-TNF treatment response in RA patients with 81% accuracy, 75% sensitivity and 86% specificity. ATRPred may aid clinicians to direct anti-TNF therapy to patients most likely to receive benefit, thus save cost as well as prevent non-responsive patients from refractory consequences. ATRPred is implemented in R.

Remote sampling of biomarkers of inflammation with linked patient generated health data in patients with rheumatic and musculoskeletal diseases: an Ecological Momentary Assessment feasibility study.

BACKGROUND: People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation. METHODS: Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7). RESULTS: Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon. CONCLUSIONS: Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.

Anti-tumour necrosis factor-alpha response associated with combined CD226 and HLA-DRB1[*]0404 haplotype in rheumatoid arthritis.

OBJECTIVES: Predicting response to anti-tumour necrosis factor alpha (anti-TNFα) drugs at baseline remains an elusive goal in rheumatoid arthritis (RA) management. The purpose of this study was to determine if baseline genetic variants of PTPRC, AFF3, myD228, CHUK, MTHFR1, MTHFR2, CD226 and a number of KIR and HLA alleles could predict response to anti-TNF-α in rheumatoid arthritis patients. METHODS: Peripheral blood samples were collected from 238 RA patients treated with anti-TNFα drugs. Genotyping was performed using biochip array technology by Randox Laboratories Ltd. and sequence specific polymerase chain reaction. Linear regression analysis was performed to investigate the role of these genotypes in predicting response to treatment, as defined by European League Against Rheumatism (EULAR) response classification and absolute change in disease activity score (DAS28). RESULTS: Of 238 RA patients analysed, 50.4% received adalimumab, 29.7% received etanercept, 14.8% received infliximab, 3.4% certoluzimab and 1.7% golimumab. The MTHFR1 variant rs1801133 was significantly associated with the EULAR response, p=0.044. Patients with the HLA-DRB1*0404 allele displayed a significantly larger reduction in DAS28 compared to non-carriers (mean -2.22, -1.67 respectively, p=0.033). CD226 rs763361 was the only SNP variant significantly associated with ΔDAS28 (p=0.029). CONCLUSIONS: This study has investigated individual allele associations with reductions in DAS28 across a range of anti-TNFα treatments. A combined predictive model indicates that patients with the HLA-DRB1*0404 allele and without the CD226 rs763361 polymorphism exhibit the largest reduction in DAS28 after anti-TNF-α treatment.

Development of novel methods for non-canonical myeloma protein analysis with an innovative adaptation of immunofixation electrophoresis, native top-down mass spectrometry, and middle-down de novo sequencing.

OBJECTIVES: Multiple myeloma (MM) is a malignant plasma cell neoplasm, requiring the integration of clinical examination, laboratory and radiological investigations for diagnosis. Detection and isotypic identification of the monoclonal protein(s) and measurement of other relevant biomarkers in serum and urine are pivotal analyses. However, occasionally this approach fails to characterize complex protein signatures. Here we describe the development and application of next generation mass spectrometry (MS) techniques, and a novel adaptation of immunofixation, to interrogate non-canonical monoclonal immunoproteins. METHODS: Immunoprecipitation immunofixation (IP-IFE) was performed on a Sebia Hydrasys Scan2. Middle-down de novo sequencing and native MS were performed with multiple instruments (21T FT-ICR, Q Exactive HF, Orbitrap Fusion Lumos, and Orbitrap Eclipse). Post-acquisition data analysis was performed using Xcalibur Qual Browser, ProSight Lite, and TDValidator. RESULTS: We adapted a novel variation of immunofixation electrophoresis (IFE) with an antibody-specific immunosubtraction step, providing insight into the clonal signature of gamma-zone monoclonal immunoglobulin (M-protein) species. We developed and applied advanced mass spectrometric techniques such as middle-down de novo sequencing to attain in-depth characterization of the primary sequence of an M-protein. Quaternary structures of M-proteins were elucidated by native MS, revealing a previously unprecedented non-covalently associated hetero-tetrameric immunoglobulin. CONCLUSIONS: Next generation proteomic solutions offer great potential for characterizing complex protein structures and may eventually replace current electrophoretic approaches for the identification and quantification of M-proteins. They can also contribute to greater understanding of MM pathogenesis, enabling classification of patients into new subtypes, improved risk stratification and the potential to inform decisions on future personalized treatment modalities.

State-of-the-Art Sensors for Remote Care of People with Dementia during a Pandemic: A Systematic Review.

In the last decade, there has been a significant increase in the number of people diagnosed with dementia. With diminishing public health and social care resources, there is substantial need for assistive technology-based devices that support independent living. However, existing devices may not fully meet these needs due to fears and uncertainties about their use, educational support, and finances. Further challenges have been created by COVID-19 and the need for improved safety and security. We have performed a systematic review by exploring several databases describing assistive technologies for dementia and identifying relevant publications for this review. We found there is significant need for appropriate user testing of such devices and have highlighted certifying bodies for this purpose. Given the safety measures imposed by the COVID-19 pandemic, this review identifies the benefits and challenges of existing assistive technologies for people living with dementia and their caregivers. It also provides suggestions for future research in these areas.

Exploring the Involvement of NLRP3 and IL-1ß in Osteoarthritis of the Hand: Results from a Pilot Study.

Hand osteoarthritis (HOA) includes different subsets; a particular and uncommon form is erosive HOA (EHOA). Interleukin- (IL-) 1ß plays a crucial role in the pathogenesis of osteoarthritis (OA); it is synthesized as an inactive precursor which requires the intervention of a cytosolic multiprotein complex, named inflammasome, for its activation. The aim of this study was to investigate the involvement of IL-1ß and the NOD-like receptor pyrin domain containing 3 (NLRP3) inflammasome in patients with EHOA and nonerosive HOA (NEHOA) compared to healthy controls. In particular, we evaluated the gene expression of IL-1ß and NLRP3, the serum levels of IL-1ß, IL-6, IL-17, and tumor necrosis factor- (TNF-) α, and the protein levels of IL-1ß and NLRP3. We also assessed the relationships between IL-1ß and NLRP3 and clinical, laboratory, and radiological findings. Fifty-four patients with HOA (25 EHOA and 29 NEHOA) and 20 healthy subjects were included in the study. Peripheral blood mononuclear cell (PBMC) gene and protein expressions of IL-1ß and NLRP3 were quantified by quantitative real-time PCR and western blot. IL-1ß, IL-6, IL-17, and TNF-α serum levels were determined by ELISA. IL-1ß gene expression was significantly reduced (p = 0.0208) in EHOA compared to healthy controls. NLRP3 protein levels were significantly increased in the NEHOA group versus the control (p = 0.0063) and EHOA groups (p = 0.0038). IL-1ß serum levels were not significantly different across the groups; IL-6, IL-17, and TNF-α were not detectable in any sample. IL-1ß concentrations were negatively correlated with the Kellgren-Lawrence score in the whole population (r = -0.446; p = 0.0008) and in NEHOA (r = -0.608; p = 0.004), while IL-1ß gene expression was positively correlated with the number of joint swellings in the EHOA group (r = 0.512; p = 0.011). Taken together, our results, showing poorly detectable IL-1ß concentrations and minimal inflammasome activity in the PBMCs of HOA patients, suggest a low grade of systemic inflammation in HOA. This evidence does not preclude a possible involvement of these factors at the local level.

Proteomic profile of cystic fibrosis sputum cells in adults chronically infected with Pseudomonas aeruginosa.

Lung disease is the main cause of morbidity and mortality in cystic fibrosis (CF), and involves chronic infection and perturbed immune responses. Tissue damage is mediated mostly by extracellular proteases, but other cellular proteins may also contribute to damage through their effect on cell activities and/or release into sputum fluid by means of active secretion or cell death.We employed MudPIT (multidimensional protein identification technology) to identify sputum cellular proteins with consistently altered abundance in adults with CF, chronically infected with Pseudomonas aeruginosa, compared with healthy controls. Ingenuity Pathway Analysis, Gene Ontology, protein abundance and correlation with lung function were used to infer their potential clinical significance.Differentially abundant proteins relate to Rho family small GTPase activity, immune cell movement/activation, generation of reactive oxygen species, and dysregulation of cell death and proliferation. Compositional breakdown identified high abundance of proteins previously associated with neutrophil extracellular traps. Furthermore, negative correlations with lung function were detected for 17 proteins, many of which have previously been associated with lung injury.These findings expand our current understanding of the mechanisms driving CF lung disease and identify sputum cellular proteins with potential for use as indicators of disease status/prognosis, stratification determinants for treatment prescription or therapeutic targets.

Psoriatic arthritis under a proteomic spotlight: application of novel technologies to advance diagnosis and management.

Psoriatic arthritis is a form of inflammatory arthritis that is frequently associated with psoriasis. Individuals with this disease present with heterogeneous clinical manifestations, making it challenging to diagnose and select optimal treatment strategies. Perhaps, not unsurprisingly, there are currently no molecular diagnostic or prognostic tests to confirm if a patient has the disease or predict how they may respond to therapy. Instead, a range of classification criteria have been developed, and the experience of the treating clinician is heavily relied upon. It is therefore widely accepted that there is a significant and as yet unmet need for effective molecular markers in psoriatic arthritis. Protein mediators drive disease pathogenesis and, therefore, represent logical potential biomarkers. Indeed, significant advances have recently been made by the introduction of multiplexed protein biomarker tests for monitoring disease activity in rheumatoid arthritis. At the same time, recent advances in proteomics have enhanced the capabilities for the detection and discovery of protein biomarkers. These advances offer renewed opportunities for the development of multi-protein biomarker signatures to support clinical decision-making in the diagnosis, prognosis and treatment of psoriatic arthritis. This review summarises the pathogenesis of psoriatic arthritis, highlighting specific areas of unmet clinical need. Furthermore, it seeks to illustrate how the latest developments in proteomic technologies could be used to enhance our understanding of the molecular pathology of psoriatic arthritis and improve clinical outcomes and quality of life for patients.

Keratinocyte growth factor promotes epithelial survival and resolution in a human model of lung injury.

RATIONALE: Increasing epithelial repair and regeneration may hasten resolution of lung injury in patients with the acute respiratory distress syndrome (ARDS). In animal models of ARDS, keratinocyte growth factor (KGF) reduces injury and increases epithelial proliferation and repair. The effect of KGF in the human alveolus is unknown. OBJECTIVES: To test whether KGF can attenuate alveolar injury in a human model of ARDS. METHODS: Volunteers were randomized to intravenous KGF (60 µg/kg) or placebo for 3 days, before inhaling 50 µg LPS. Six hours later, subjects underwent bronchoalveolar lavage (BAL) to quantify markers of alveolar inflammation and cell-specific injury. MEASUREMENTS AND MAIN RESULTS: KGF did not alter leukocyte infiltration or markers of permeability in response to LPS. KGF increased BAL concentrations of surfactant protein D, matrix metalloproteinase (MMP)-9, IL-1Ra, granulocyte-macrophage colony-stimulating factor (GM-CSF), and C-reactive protein. In vitro, BAL fluid from KGF-treated subjects inhibited pulmonary fibroblast proliferation, but increased alveolar epithelial proliferation. Active MMP-9 increased alveolar epithelial wound repair. Finally, BAL from the KGF-pretreated group enhanced macrophage phagocytic uptake of apoptotic epithelial cells and bacteria compared with BAL from the placebo-treated group. This effect was blocked by inhibiting activation of the GM-CSF receptor. CONCLUSIONS: KGF treatment increases BAL surfactant protein D, a marker of type II alveolar epithelial cell proliferation in a human model of acute lung injury. Additionally, KGF increases alveolar concentrations of the antiinflammatory cytokine IL-1Ra, and mediators that drive epithelial repair (MMP-9) and enhance macrophage clearance of dead cells and bacteria (GM-CSF). Clinical trial registered with ISRCTN 98813895.

Potential Plasma Proteins (LGALS9, LAMP3, PRSS8 and AGRN) as Predictors of Hospitalisation Risk in COVID-19 Patients.

Background: The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. Methods: We investigated the proteomic and genomic profile of COVID-19-positive patients (n = 400 for proteomics, n = 483 for genomics), focusing on differential regulation between hospitalised and non-hospitalised COVID-19 patients. Signatures had their predictive capabilities tested using independent machine learning models such as Support Vector Machine (SVM), Random Forest (RF) and Logistic Regression (LR). Results: This study has identified 224 differentially expressed proteins involved in various inflammatory and immunological pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. LGALS9 (p-value < 0.001), LAMP3 (p-value < 0.001), PRSS8 (p-value < 0.001) and AGRN (p-value < 0.001) were identified as the most statistically significant proteins. Several hundred rsIDs were queried across the top 10 significant signatures, identifying three significant SNPs on the FSTL3 gene showing a correlation with hospitalisation status. Conclusions: Our study has not only identified key signatures of COVID-19 patients with worsened health but has also demonstrated their predictive capabilities as potential biomarkers, which suggests a staple role in the worsened health effects caused by COVID-19.

Genomic, Proteomic, and Phenotypic Biomarkers of COVID-19 Severity: Protocol for a Retrospective Observational Study.

BACKGROUND: Health organizations and countries around the world have found it difficult to control the spread of COVID-19. To minimize the future impact on the UK National Health Service and improve patient care, there is a pressing need to identify individuals who are at a higher risk of being hospitalized because of severe COVID-19. Early targeted work was successful in identifying angiotensin-converting enzyme-2 receptors and type II transmembrane serine protease dependency as drivers of severe infection. Although a targeted approach highlights key pathways, a multiomics approach will provide a clearer and more comprehensive picture of severe COVID-19 etiology and progression. OBJECTIVE: The COVID-19 Response Study aims to carry out an integrated multiomics analysis to identify biomarkers in blood and saliva that could contribute to host susceptibility to SARS-CoV-2 and the development of severe COVID-19. METHODS: The COVID-19 Response Study aims to recruit 1000 people who recovered from SARS-CoV-2 infection in both community and hospital settings on the island of Ireland. This protocol describes the retrospective observational study component carried out in Northern Ireland (NI; Cohort A); the Republic of Ireland cohort will be described separately. For all NI participants (n=519), SARS-CoV-2 infection has been confirmed by reverse transcription-quantitative polymerase chain reaction. A prospective Cohort B of 40 patients is also being followed up at 1, 3, 6, and 12 months postinfection to assess longitudinal symptom frequency and immune response. Data will be sourced from whole blood, saliva samples, and clinical data from the electronic care records, the general health questionnaire, and a 12-item general health questionnaire mental health survey. Saliva and blood samples were processed to extract DNA and RNA before whole-genome sequencing, RNA sequencing, DNA methylation analysis, microbiome analysis, 16S ribosomal RNA gene sequencing, and proteomic analysis were performed on the plasma. Multiomics data will be combined with clinical data to produce sensitive and specific prognostic models for severity risk. RESULTS: An initial demographic and clinical profile of the NI Cohort A has been completed. A total of 249 hospitalized patients and 270 nonhospitalized patients were recruited, of whom 184 (64.3%) were female, and the mean age was 45.4 (SD 13) years. High levels of comorbidity were evident in the hospitalized cohort, with cardiovascular disease and metabolic and respiratory disorders being the most significant (P<.001), grouped according to the International Classification of Diseases 10 codes. CONCLUSIONS: This study will provide a comprehensive opportunity to study the mechanisms of COVID-19 severity in recontactable participants. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50733.

Senescence Biomarkers CKAP4 and PTX3 Stratify Severe Kidney Disease Patients.

INTRODUCTION: Cellular senescence is the irreversible growth arrest subsequent to oncogenic mutations, DNA damage, or metabolic insult. Senescence is associated with ageing and chronic age associated diseases such as cardiovascular disease and diabetes. The involvement of cellular senescence in acute kidney injury (AKI) and chronic kidney disease (CKD) is not fully understood. However, recent studies suggest that such patients have a higher-than-normal level of cellular senescence and accelerated ageing. METHODS: This study aimed to discover key biomarkers of senescence in AKI and CKD patients compared to other chronic ageing diseases in controls using OLINK proteomics. RESULTS: We show that senescence proteins CKAP4 (p-value < 0.0001) and PTX3 (p-value < 0.0001) are upregulated in AKI and CKD patients compared with controls with chronic diseases, suggesting the proteins may play a role in overall kidney disease development. CONCLUSIONS: CKAP4 was found to be differentially expressed in both AKI and CKD when compared to UHCs; hence, this biomarker could be a prognostic senescence biomarker of both AKI and CKD.

Analysis of SARS-CoV-2 antibody seroprevalence in Northern Ireland during 2020-2021.

Background: With the spread of SARS-CoV-2 impacting upon public health directly and socioeconomically, further information was required to inform policy decisions designed to limit virus spread during the pandemic. This study sought to contribute to serosurveillance work within Northern Ireland to track SARS-CoV-2 progression and guide health strategy. Methods: Sera/plasma samples from clinical biochemistry laboratories were analysed for anti-SARS-CoV-2 antibodies. Samples were assessed using an Elecsys anti-SARS-CoV-2 or anti-SARS-CoV-2 S ECLIA (Roche) on an automated cobas e 801 analyser. Samples were also assessed via an anti-SARS-CoV-2 ELISA (Euroimmun). A subset of samples assessed via the Elecsys anti-SARS-CoV-2 ECLIA were subsequently analysed in an ACE2 pseudoneutralisation assay using a V-PLEX SARS-CoV-2 Panel 7 for IgG and ACE2 (Meso Scale Diagnostics). Results: Across three testing rounds (June-July 2020, November-December 2020 and June-July 2021 (rounds 1-3 respectively)), 4844 residual sera/plasma specimens were assayed for anti-SARS-CoV-2 antibodies. Seropositivity rates increased across the study, peaking at 11.6 % (95 % CI 10.4 %-13.0 %) during round 3. Varying trends in SARS-CoV-2 seropositivity were noted based on demographic factors. For instance, highest rates of seropositivity shifted from older to younger demographics across the study period. In round 3, Alpha (B.1.1.7) variant neutralising antibodies were most frequently detected across age groups, with median concentration of anti-spike protein antibodies elevated in 50-69 year olds and anti-S1 RBD antibodies elevated in 70+ year olds, relative to other age groups. Conclusions: With seropositivity rates of <15 % across the assessment period, it can be concluded that the significant proportion of the Northern Ireland population had not yet naturally contracted the virus by mid-2021.

An AI Approach to Identifying Novel Therapeutics for Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that has a significant impact on quality of life and work capacity. Treatment of RA aims to control inflammation and alleviate pain; however, achieving remission with minimal toxicity is frequently not possible with the current suite of drugs. This review aims to summarise current treatment practices and highlight the urgent need for alternative pharmacogenomic approaches for novel drug discovery. These approaches can elucidate new relationships between drugs, genes, and diseases to identify additional effective and safe therapeutic options. This review discusses how computational approaches such as connectivity mapping offer the ability to repurpose FDA-approved drugs beyond their original treatment indication. This review also explores the concept of drug sensitisation to predict co-prescribed drugs with synergistic effects that produce enhanced anti-disease efficacy by involving multiple disease pathways. Challenges of this computational approach are discussed, including the availability of suitable high-quality datasets for comprehensive analysis and other data curation issues. The potential benefits include accelerated identification of novel drug combinations and the ability to trial and implement established treatments in a new index disease. This review underlines the huge opportunity to incorporate disease-related data and drug-related data to develop methods and algorithms that have strong potential to determine novel and effective treatment regimens.

Biomarkers in rheumatology, now and in the future.

This review examines the biomarker development process by using rheumatic disorders as the disease model for discussion. We evaluate the current role of biomarkers in the practice of rheumatology and discuss their likely role in the future. We define the essential components of the biomarker development pipeline and discuss the issue of fitness for purpose, i.e. what the biomarker(s) might offer in a clinical setting. As a component of this review we also highlight several emerging technologies that are beginning to provide practical solutions to support biomarker validation. In the process, we highlight some scenarios where additional biomarkers would add considerable value to clinical practice, and we review appropriate methods for each. We also emphasize some important but infrequently discussed considerations, including the need for protein variant verification. Ultimately, the adroit application of the methods of proteomics will transform the practice rheumatology and allow personalized clinical practice to become a reality.

CD169+ Monocyte and Regulatory T Cell Subsets Are Associated with Disease Activity in Rheumatoid Arthritis.

Disease activity in rheumatoid arthritis (RA) is influenced by activation of circulating and synovial immune cells. Regulatory T cells (Tregs) and monocytes are key cells that drive inflammation in RA. This study investigated if a relationship exists between disease activity in RA and circulating Treg and monocyte numbers and phenotypes. A potential sialic acid (Sia) mediated link between Tregs and monocytes was also probed in vitro. Peripheral blood mononuclear cells (PBMCs) were isolated from RA patient (n = 62) and healthy control (n = 21) blood using density gradient separation. Flow cytometry was used to count and phenotype Treg and monocyte subsets, and to sort healthy control Tregs for Sia cell culture experiments. The effects of Sia on activated Treg FoxP3 and NFκB expression was assessed by flow cytometry and concentrations of secreted TNFα, IL-10 and IFNγ determined by ELISA. High disease activity RA patients who were unresponsive to disease modifying anti-rheumatic drugs (n = 31), have significantly lower relative numbers (percentages) of CD4+CD25+CD127− Tregs (p < 0.01) and memory CD45RA−FoxP3+ Tregs (p < 0.01), compared to low disease activity responders (n = 24). Relative numbers of non-classical CD169+ monocytes are associated with disease activity in RA (p = 0.012). Sia reduced Treg expression of FoxP3, NFκB and cytokines in vitro. A strong association has been identified between non-classical CD169+ monocytes and post-treatment disease activity in RA. This study also indicates that Sia can reduce Treg activation and cytokine release. We postulate that such a reduction could be mediated by interaction with sialyted proteins captured by CD169+ monocytes.

Role of Senescence and Aging in SARS-CoV-2 Infection and COVID-19 Disease.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic associated with substantial morbidity and mortality worldwide, with particular risk for severe disease and mortality in the elderly population. SARS-CoV-2 infection is driven by a pathological hyperinflammatory response which results in a dysregulated immune response. Current advancements in aging research indicates that aging pathways have fundamental roles in dictating healthspan in addition to lifespan. Our review discusses the aging immune system and highlights that senescence and aging together, play a central role in COVID-19 pathogenesis. In our review, we primarily focus on the immune system response to SARS-CoV-2 infection, the interconnection between severe COVID-19, immunosenescence, aging, vaccination, and the emerging problem of Long-COVID. We hope to highlight the importance of identifying specific senescent endotypes (or "sendotypes"), which can used as determinants of COVID-19 severity and mortality. Indeed, identified sendotypes could be therapeutically exploited for therapeutic intervention. We highlight that senolytics, which eliminate senescent cells, can target aging-associated pathways and therefore are proving attractive as potential therapeutic options to alleviate symptoms, prevent severe infection, and reduce mortality burden in COVID-19 and thus ultimately enhance healthspan.

Assessment of a dried blood spot C-reactive protein method to identify disease flares in rheumatoid arthritis patients.

Rheumatoid arthritis (RA) is characterised by painful, stiff and swollen joints. RA features sporadic 'flares' or inflammatory episodes-mostly occurring outside clinics-where symptoms worsen and plasma C-reactive protein (CRP) becomes elevated. Poor control of inflammation results in higher rates of irreversible joint damage, increased disability, and poorer quality of life. Flares need to be accurately identified and managed. A method comparison study was designed to assess agreement between CRP values obtained by dried blood spot (DBS) versus conventional venepuncture sampling. The ability of a weekly DBS sampling and CRP test regime to detect flare outside the clinic was also assessed. Matched venepuncture and finger lancet DBS samples were collected from n = 100 RA patients with active disease at baseline and 6 weeks (NCT02809547). A subset of n = 30 RA patients submitted weekly DBS samples over the study period. Patient demographics, including self-reported flares were recorded. DBS sample CRP measurements were made by enzyme-linked immunosorbent assay, and venepuncture samples by a reference immunoturbometric assay. Data was compared between sample types by Bland-Altman and weighted Deming regression analyses. Flare detection sensitivity and specificity were compared between 'minimal' baseline and 6 week sample CRP data and the 'continuous' weekly CRP data. Baseline DBS ELISA assay CRP measures yielded a mean positive bias of 2.693 ± 8.640 (95% limits of agreement - 14.24 to 19.63%), when compared to reference assay data. Deming regression revealed good agreement between the DBS ELISA method and reference assay data, with baseline data slope of 0.978 and intercept -0.153. The specificity of 'continuous' area under the curve (AUC) CRP data (72.7%) to identify flares, was greater than 'minimal' AUC CRP data (54.5%). This study indicates reasonable agreement between DBS and the reference method, especially at low to mid-range CRP values. Importantly, longitudinal CRP measurement in RA patients helps to clearly identify flare and thus could assist in remote monitoring strategies and may facilitate timely therapeutic intervention.Trial registration: The Remote Arthritis Disease Activity MonitoR (RADAR) study was registered on 22/06/2016 at ClinicalTrials.gov Identifier: NCT02809547. https://clinicaltrials.gov/ct2/show/NCT02809547 .