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.

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.

Abstract Background Clinical trials of anti-tumour necrosis factor alpha (TNF) have shown efficacy in 60–70% of rheumatoid arthritis patients (RA). Predicting response to anti-TNF drugs at baseline remains an elusive goal in RA management. The purpose of this study was to determine if baseline levels of circulating cytokines, soluble receptors, adhesion molecules and metabolic factors differentiate future responders. Methods RA patients (n=29) with active disease were recruited, who had failed on disease modifying drugs and were recommended for anti-TNF treatment. Peripheral blood samples were collected at baseline. Responders were identified by a ≥1.2 reduction in disease activity score (DAS28-ESR) at 6 months. Five protein arrays quantified 33 proteins in pre-treatment plasma (Cytokine I, III and IV; Metabolic I; Adhesion molecule; Randox Laboratories Ltd., UK). Data was analysed by Pearson ranked correlation and logistic regression to clinical measures of disease activity at baseline and six months anti-TNF treatment. Results Elevated levels of interleukin 8 (p=0.043), monocyte chemoattractant protein (p=0.027), granulocyte-macrophage colony-stimulating factor (p=0.020) and soluble interleukin 2α receptor (p=0.01) were associated with high TJC at baseline. No significant relationship with the protein array panels was recorded relative to baseline DAS28-ESR. Significant inverse correlations were observed between absolute change in DAS28-ESR after 6 months of anti-TNF therapy and baseline levels of interleukin 6 (p=0.026) and resistin (p=0.044). Conclusions These findings suggest that baseline levels of specific circulating proteins may help to differentiate RA patient responders to anti-TNF therapies.

The identification of patients who will respond to anti-tumor necrosis factor alpha (anti-TNF-α) therapy will improve the efficacy, safety, and economic impact of these agents. We investigated whether killer cell immunoglobulin-like receptor (KIR) genes are related to response to anti-TNF-α therapy in patients with rheumatoid arthritis (RA). Sixty-four RA patients and 100 healthy controls were genotyped for 16 KIR genes and human leukocyte antigen-C (HLA-C) group 1/2 using polymerase chain reaction sequence-specific oligonucleotide probes (PCR-SSOP). Each patient received anti-TNF-α therapy (adalimumab, etanercept, or infliximab), and clinical responses were evaluated after 3 months using the disease activity score in 28 joints (DAS28). We investigated the correlations between the carriership of KIR genes, HLA-C group 1/2 genes, and clinical data with response to therapy. Patients responding to therapy showed a significantly higher frequency of KIR2DS2/KIR2DL2 (67.7% R vs. 33.3% NR; P = 0.012). A positive clinical outcome was associated with an activating KIR–HLA genotype; KIR2DS2 + HLA-C group 1/2 homozygous. Inversely, non-response was associated with the relatively inhibitory KIR2DS2 – HLA-C group 1/2 heterozygous genotype. The KIR and HLA-C genotype of an RA patient may provide predictive information for response to anti-TNF-α therapy.

We report a clinical trial using musculoskeletal ultrasound (MSUS) to assess primary knee osteoarthritis (OA). Evidence demonstrates a positive therapeutic effect of intra‐articular corticosteroid ...