Positive airway pressure longer than 24 h is associated with histopathological volutrauma in severe COVID-19 pneumonia—an ESGFOR based narrative case-control review

SARS-CoV-2; Post-mortem microbiology; VolutraumaSARS-CoV-2; Microbiología post mortem; VolutraumaSARS-CoV-2; Microbiologia post mortem; VolutraumaBackground and Objective: A thorough understanding of the pathogenic mechanisms elicited by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still requires further research. Until recently, only a restricted number of autopsies have been performed, therefore limiting the accurate knowledge of the lung injury associated with SARS-CoV-2. A multidisciplinary European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group of Forensic and Post-mortem Microbiology-ESGFOR team conducted a non-systematic narrative literature review among coronavirus 2019 disease (COVID-19) pneumonia cases assessing the histopathological (HP) effects of positive airways pressure. HP lung features were recorded and compared between mechanically ventilated (>24 hours) and control (ventilation <24 hours) patients. A logistic regression analysis was performed to identify associations between mechanical ventilation (MV) and HP findings. Methods: A PubMed and MEDLINE search was conducted in order to identify studies published between March 1st 2020 and June 30th 2021. Key Content and Findings: Seventy patients (median age: 69 years) from 24 studies were analysed, among whom 38 (54.2%) underwent MV longer than 24 hours. Overall, main HP features were: diffuse alveolar damage (DAD) in 53 (75.7%), fibrosis (interstitial/intra-alveolar) in 43 (61.4%), vascular damage—including thrombosis/emboli- in 41 (58.5%), and endotheliitis in only 8 (11.4%) patients. Association of DAD, fibrosis and vascular damage was detected in 30 (42.8%) patients. Multivariate analysis, adjusted by age and gender, identified MV >24 hours as an independent variable associated with DAD (OR =5.40, 95% CI: 1.48–19.62), fibrosis (OR =3.88, 95% CI: 1.25–12.08), vascular damage (OR =5.49, 95% CI: 1.78–16.95) and association of DAD plus fibrosis plus vascular damage (OR =6.99, 95% CI: 2.04–23.97). Conclusions: We identified that patients mechanically ventilated >24 hours had a significantly higher rate of pulmonary injury on histopathology independently of age and gender. Our findings emphasize the importance of maintaining a protective ventilator strategy when subjects with COVID-19 pneumonia undergo intubation

Development and validation of a multivariate predictive model for rheumatoid arthritis mortality using a machine learning approach

We developed and independently validated a rheumatoid arthritis (RA) mortality prediction model using the machine learning method Random Survival Forests (RSF). Two independent cohorts from Madrid (Spain) were used: the Hospital Cl&iacute;nico San Carlos RA Cohort (HCSC-RAC; training; 1,461 patients), and the Hospital Universitario de La Princesa Early Arthritis Register Longitudinal study (PEARL; validation; 280 patients). Demographic and clinical-related variables collected during the first two years after disease diagnosis were used. 148 and 21 patients from HCSC-RAC and PEARL died during a median follow-up time of 4.3 and 5.0&nbsp;years, respectively. Age at diagnosis, median erythrocyte sedimentation rate, and number of hospital admissions showed the higher predictive capacity. Prediction errors in the training and validation cohorts were 0.187 and 0.233, respectively. A survival tree identified five mortality risk groups using the predicted ensemble mortality. After 1 and 7 years of follow-up, time-dependent specificity and sensitivity in the validation cohort were 0.79&ndash;0.80 and 0.43&ndash;0.48, respectively, using the cut-off value dividing the two lower risk categories. Calibration curves showed overestimation of the mortality risk in the validation cohort. In conclusion, we were able to develop a clinical prediction model for RA mortality using RSF, providing evidence for further work on external validation

A predominant involvement of the triple seropositive patients and others with rheumatoid factor in the association of smoking with rheumatoid arthritis

The major environmental risk factor for rheumatoid arthritis (RA) is smoking, which according to a widely accepted model induces protein citrullination in the lungs, triggering the production of anticitrullinated protein antibodies (ACPA) and RA development. Nevertheless, some research findings do not fit this model. Therefore, we obtained six independent cohorts with 2253 RA patients for a detailed analysis of the association between smoking and RA autoantibodies. Our results showed a predominant association of smoking with the concurrent presence of the three antibodies: rheumatoid factor (RF), ACPA and anti-carbamylated protein antibodies (ACarPA) (3 Ab vs. 0 Ab: OR = 1.99, p = 2.5 × 10?8). Meta-analysis with previous data (4491 patients) confirmed the predominant association with the concurrent presence of the three antibodies (3 Ab vs. 0 Ab: OR = 2.00, p = 4.4 ×10?16) and revealed that smoking was exclusively associated with the presence of RF in patients with one or two antibodies (RF+ 1+2 vs. RF? 0+1+2: OR = 1.32, p = 0.0002). In contrast, no specific association with ACPA or ACarPA was found. Therefore, these results showed the need to understand how smoking favors the concordance of RA specific antibodies and RF triggering, perhaps involving smoking-induced epitope spreading and other hypothesized mechanisms

Genome-wide pathway analysis identifies oxidative stress related gene MSRA as rheumatoid arthritis susceptibility locus

Objective: Genome-wide association studies (GWASs) carried out in rheumatoid arthritis (RA) have led to the discovery of several genetic associations with this disease. Still, the current associated genetic variations can explain only part of the genetic risk involved in RA, and it is well recognised that these GWASs are likely underpowered to detect all common disease variants. Therefore, we explored the genomic regions showing low-significance associations in previous GWASs of RA. Methods: To reduce the false-positive signal fraction, we exploited pathway analysis to prioritise regions containing genes most likely to be implicated in RA. We hypothesised that true disease genes would be in a similar pathway. Therefore, genes from similar pathways but located in different regions were prioritised for replication using Prioritizer software. 384 genetic variants selected from previous RA GWASs were tested in a Spanish case/control discovery cohort comprising 376 RA patients and 478 healthy controls for replication. Statistically significant associations were further validated in replication cohorts from Spain and Netherlands, up to a total of 1,818 RA patients and 2,498 controls. Results: We detected a novel genetic association between RA and the MSRA gene (rs10903323, P = 2.91×10-5, OR = 1.51) in the Spanish combined population. This association was further tested in our independent Dutch replication cohort. Combined analysis showed an overall association of MSRA with RA (P = 2.19×10-4, OR = 1.28). Conclusion: Novel association in the MSRA gene related to oxidative stress is described herein and support a major role for this process in RA

Identification of IRX1 as a Risk Locus for Rheumatoid Factor Positivity in Rheumatoid Arthritis in a Genome-Wide Association Study.

Rheumatoid factor (RF) is a well-established diagnostic and prognostic biomarker in rheumatoid arthritis (RA). However, ∼20% of RA patients are negative for this anti-IgG antibody. To date, only variation at the HLA-DRB1 gene has been associated with the presence of RF. This study was undertaken to identify additional genetic variants associated with RF positivity. A genome-wide association study (GWAS) for RF positivity was performed using an Illumina Quad610 genotyping platform. A total of 937 RF-positive and 323 RF-negative RA patients were genotyped for >550,000 single-nucleotide polymorphisms (SNPs). Association testing was performed using an allelic chi-square test implemented in Plink software. An independent cohort of 472 RF-positive and 190 RF-negative RA patients was used to validate the most significant findings. In the discovery stage, a SNP in the IRX1 locus on chromosome 5p15.3 (SNP rs1502644) showed a genome-wide significant association with RF positivity (P = 4.13 × 10(-8) , odds ratio [OR] 0.37 [95% confidence interval (95% CI) 0.26-0.53]). In the validation stage, the association of IRX1 with RF was replicated in an independent group of RA patients (P = 0.034, OR 0.58 [95% CI 0.35-0.97] and combined P = 1.14 × 10(-8) , OR 0.43 [95% CI 0.32-0.58]). To our knowledge, this is the first GWAS of RF positivity in RA. Variation at the IRX1 locus on chromosome 5p15.3 is associated with the presence of RF. Our findings indicate that IRX1 and HLA-DRB1 are the strongest genetic factors for RF production in RA