CD19 + CD21lo/neg cells are increased in systemic sclerosis-associated interstitial lung disease

Interstitial lung disease (ILD) represents a significant cause of morbidity and mortality in systemic sclerosis (SSc). The purpose of this study was to examine recirculating lymphocytes from SSc patients for potential biomarkers of interstitial lung disease (ILD). Peripheral blood mononuclear cells (PBMCs) were isolated from patients with SSc and healthy controls enrolled in the Vanderbilt University Myositis and Scleroderma Treatment Initiative Center cohort between 9/2017–6/2019. Clinical phenotyping was performed by chart abstraction. Immunophenotyping was performed using both mass cytometry and fluorescence cytometry combined with t-distributed stochastic neighbor embedding analysis and traditional biaxial gating. This study included 34 patients with SSc-ILD, 14 patients without SSc-ILD, and 25 healthy controls. CD21^lo/neg cells are significantly increased in SSc-ILD but not in SSc without ILD (15.4 ± 13.3% vs. 5.8 ± 0.9%, p = 0.002) or healthy controls (5.0 ± 0.5%, p < 0.0001). While CD21^lo/neg B cells can be identified from a single biaxial gate, tSNE analysis reveals that the biaxial gate is comprised of multiple distinct subsets, all of which are increased in SSc-ILD. CD21^lo/neg cells in both healthy controls and SSc-ILD are predominantly tBET positive and do not have intracellular CD21. Immunohistochemistry staining demonstrated that CD21^lo/neg B cells diffusely infiltrate the lung parenchyma of an SSc-ILD patient. Additional work is needed to validate this biomarker in larger cohorts and longitudinal studies and to understand the role of these cells in SSc-ILD.

     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

COVID-19 Gender Disparities and Mitigation Recommendations: A Narrative Review

The coronavirus disease 2019 (COVID-19) pandemic has rapidly created widespread impacts on global health and the economy. Data suggest that women are less susceptible to severe illness. However, sex-disaggregated data are incomplete, leaving room for misinterpretation, and focusing only on biologic sex underestimates the gendered impact of the pandemic on women. This narrative review summarizes what is known about gender disparities during the COVID-19 pandemic and the economic, domestic, and health burdens along with overlapping vulnerabilities related to the pandemic. In addition, this review outlines recommended strategies that advocacy groups, community leaders, and policymakers should implement to mitigate the widening gender disparities related to COVID-19.     

Hip Displacement in Cerebral Palsy: The Role of Surveillance

IntroductionHip displacement is common in cerebral palsy (CP) and is related to the severity of neurological and functional impairment. It is a silent, but progressive disease, and can result in significant morbidity and decreased quality of life, if left untreated. The pathophysiology of hip displacement in CP is a combination of hip flexor-adductor muscle spasticity, abductor muscle weakness, and delayed weight-bearing, resulting in proximal femoral deformities and progressive acetabular dysplasia. Due to a lack of symptoms in the early stages of hip displacement, the diagnosis is easily missed. Awareness of this condition and regular surveillance by clinical examination and serial radiographs of the hips are the key to early diagnosis and treatment.Hip surveillance programmesSeveral population-based studies from around the world have demonstrated that universal hip surveillance in children with CP allows early detection of hip displacement and appropriate early intervention, with a resultant decrease in painful dislocations. Global hip surveillance models are based upon the patients’ age, functional level determined by the Gross Motor Function Classification system (GMFCS), gait classification, standardized clinical exam, and radiographic indices such as the migration percentage (MP), as critical indicators of progressive hip displacement.ConclusionDespite 25 years of evidence showing the efficacy of established hip surveillance programmes, there is poor awareness among healthcare professionals in India about the importance of regular hip surveillance in children with CP. There is a need for professional organizations to develop evidence-based guidelines for hip surveillance which are relevant to the Indian context.