Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response

BACKGROUND. The identification and treatment of individuals with tuberculosis (TB) is a global public health priority. Accurate diagnosis of pulmonary active TB (ATB) disease remains challenging and relies on extensive medical evaluation and detection of Mycobacterium tuberculosis (Mtb) in the patient’s sputum. Further, the response to treatment is monitored by sputum culture conversion, which takes several weeks for results. Here, we sought to identify blood-based host biomarkers associated with ATB and hypothesized that immune activation markers on Mtb-specific CD4⁺ T cells would be associated with Mtb load in vivo and could thus provide a gauge of Mtb infection.METHODS. Using polychromatic flow cytometry, we evaluated the expression of immune activation markers on Mtb-specific CD4⁺ T cells from individuals with asymptomatic latent Mtb infection (LTBI) and ATB as well as from ATB patients undergoing anti-TB treatment.RESULTS. Frequencies of Mtb-specific IFN-γ⁺CD4⁺ T cells that expressed immune activation markers CD38 and HLA-DR as well as intracellular proliferation marker Ki-67 were substantially higher in subjects with ATB compared with those with LTBI. These markers accurately classified ATB and LTBI status, with cutoff values of 18%, 60%, and 5% for CD38⁺IFN-γ⁺, HLA-DR⁺IFN-γ⁺, and Ki-67⁺IFN-γ⁺, respectively, with 100% specificity and greater than 96% sensitivity. These markers also distinguished individuals with untreated ATB from those who had successfully completed anti-TB treatment and correlated with decreasing mycobacterial loads during treatment.CONCLUSION. We have identified host blood-based biomarkers on Mtb-specific CD4⁺ T cells that discriminate between ATB and LTBI and provide a set of tools for monitoring treatment response and cure.TRIAL REGISTRATION. Registration is not required for observational studies.FUNDING. This study was funded by Emory University, the NIH, and the Yerkes National Primate Center.     

Pathophysiology and management of sensitive skin: position paper from the special interest group on sensitive skin of the International Forum for the Study of Itch (IFSI)

The special interest group on sensitive skin of the International Forum for the Study of Itch previously defined sensitive skin as a syndrome defined by the occurrence of unpleasant sensations (stinging, burning, pain, pruritus and tingling sensations) in response to stimuli that normally should not provoke such sensations. This additional paper focuses on the pathophysiology and the management of sensitive skin. Sensitive skin is not an immunological disorder but is related to alterations of the skin nervous system. Skin barrier abnormalities are frequently associated, but there is no cause and direct relationship. Further studies are needed to better understand the pathophysiology of sensitive skin – as well as the inducing factors. Avoidance of possible triggering factors and the use of well-tolerated cosmetics, especially those containing inhibitors of unpleasant sensations, might be suggested for patients with sensitive skin. The role of psychosocial factors, such as stress or negative expectations, might be relevant for subgroups of patients. To date, there is no clinical trial supporting the use of topical or systemic drugs in sensitive skin. The published data are not sufficient to reach a consensus on sensitive skin management. In general, patients with sensitive skin require a personalized approach, taking into account various biomedical, neural and psychosocial factors affecting sensitive skin.     

Combinatorial Inhibition of Myostatin and Activin A Improves Femoral Bone Properties in the G610C Mouse Model of Osteogenesis Imperfecta

Osteogenesis imperfecta (OI) is a collagen-related bone disorder characterized by fragile osteopenic bone and muscle weakness. We have previously shown that the soluble activin receptor type IIB decoy (sActRIIB) molecule increases muscle mass and improves bone strength in the mild to moderate G610C mouse model of OI. The sActRIIB molecule binds multiple transforming growth factor-β (TGF-β) ligands, including myostatin and activin A. Here, we investigate the musculoskeletal effects of inhibiting activin A alone, myostatin alone, or both myostatin and activin A in wild-type (Wt) and heterozygous G610C (+/G610C) mice using specific monoclonal antibodies. Male and female Wt and +/G610C mice were treated twice weekly with intraperitoneal injections of monoclonal control antibody (Ctrl-Ab, Regn1945), anti-activin A antibody (ActA-Ab, Regn2476), anti-myostatin antibody (Mstn-Ab, Regn647), or both ActA-Ab and Mstn-Ab (Combo, Regn2476, and Regn647) from 5 to 16 weeks of age. Prior to euthanasia, whole body composition, metabolism and muscle force generation assessments were performed. Post euthanasia, hindlimb muscles were evaluated for mass, and femurs were evaluated for changes in microarchitecture and biomechanical strength using micro–computed tomography (μCT) and three-point bend analyses. ActA-Ab treatment minimally impacted the +/G610C musculoskeleton, and was detrimental to bone strength in male +/G610C mice. Mstn-Ab treatment, as previously reported, resulted in substantial increases in hindlimb muscle weights and overall body weights in Wt and male +/G610C mice, but had minimal skeletal impact in +/G610C mice. Conversely, the Combo treatment outperformed ActA-Ab alone or Mstn-Ab alone, consistently increasing hindlimb muscle and body weights regardless of sex or genotype and improving bone microarchitecture and strength in both male and female +/G610C and Wt mice. Combinatorial inhibition of activin A and myostatin more potently increased muscle mass and bone microarchitecture and strength than either antibody alone, recapturing most of the observed benefits of sActRIIB treatment in +/G610C mice. © 2022 American Society for Bone and Mineral Research (ASBMR).     

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.