Plasma Acute Phase Proteins as Predictors of Chronic Lung Allograft Dysfunction in Lung Transplant Recipients

Serum Ceruloplasmin-to-Albumin Ratio as a Biochemical Marker in Pulmonary Tuberculosis Before and After Treatment

BACKGROUND

The study compares the serum ceruloplasmin-to-albumin ratio of tuberculosis (TB) patients before and after anti-tuberculosis treatment (ATT) to assess its diagnostic and prognostic value. Despite the pandemic's impact on TB notifications, global TB cases rose by 16% in 2022.

METHODS

The study was conducted at Meenakshi Medical College Hospital and Research Institute, Kanchipuram, from November 2022 to November 2023, with participants aged 15 and above diagnosed with pulmonary TB. The analysis of clinical, radiographic, microbiological, and biochemical data revealed a gender distribution of 58% male and 42% female individuals, with an average age of 49. Significant reductions in ceruloplasmin levels and increases in albumin levels were found following therapy, as well as a decrease in the ceruloplasmin-to-albumin ratio, showing that ceruloplasmin may serve as a severity measure and treatment indicator.

RESULTS

Male patients accounted for 58% of the study population, while females accounted for 42%. Patients aged 36-45 made up the largest group (26%). Following treatment, serum ceruloplasmin levels decreased significantly (from 66.28 mg/dL to 35.56 mg/dL), but albumin levels increased (from 2.96 g/dL to 4.19 g/dL). The ceruloplasmin-to-albumin ratio dropped from 0.022 to 0.008, showing treatment efficacy.

CONCLUSIONS

The study highlights the potential of serum biomarkers for diagnosing and monitoring TB. The serum ceruloplasmin-to-albumin ratio is a promising biochemical diagnostic. Further research is needed to validate these findings and investigate their clinical significance in TB management.

Systems prediction of chronic lung allograft dysfunction: Results and perspectives from the Cohort of Lung Transplantation and Systems prediction of Chronic Lung Allograft Dysfunction cohorts

Background

Chronic lung allograft dysfunction (CLAD) is the leading cause of poor long-term survival after lung transplantation (LT). Systems prediction of Chronic Lung Allograft Dysfunction (SysCLAD) aimed to predict CLAD.

Methods

To predict CLAD, we investigated the clinicome of patients with LT; the exposome through assessment of airway microbiota in bronchoalveolar lavage cells and air pollution studies; the immunome with works on activation of dendritic cells, the role of T cells to promote the secretion of matrix metalloproteinase-9, and subpopulations of T and B cells; genome polymorphisms; blood transcriptome; plasma proteome studies and assessment of MSK1 expression.

Results

Clinicome: the best multivariate logistic regression analysis model for early-onset CLAD in 422 LT eligible patients generated a ROC curve with an area under the curve of 0.77. Exposome: chronic exposure to air pollutants appears deleterious on lung function levels in LT recipients (LTRs), might be modified by macrolides, and increases mortality. Our findings established a link between the lung microbial ecosystem, human lung function, and clinical stability post-transplant. Immunome: a decreased expression of CLEC1A in human lung transplants is predictive of the development of chronic rejection and associated with a higher level of interleukin 17A; Immune cells support airway remodeling through the production of plasma MMP-9 levels, a potential predictive biomarker of CLAD. Blood CD9-expressing B cells appear to favor the maintenance of long-term stable graft function and are a potential new predictive biomarker of BOS-free survival. An early increase of blood CD4 + CD57 + ILT2+ T cells after LT may be associated with CLAD onset. Genome: Donor Club cell secretory protein G38A polymorphism is associated with a decreased risk of severe primary graft dysfunction after LT. Transcriptome: blood POU class 2 associating factor 1, T-cell leukemia/lymphoma domain, and B cell lymphocytes, were validated as predictive biomarkers of CLAD phenotypes more than 6 months before diagnosis. Proteome: blood A2MG is an independent predictor of CLAD, and MSK1 kinase overexpression is either a marker or a potential therapeutic target in CLAD.

Conclusion

Systems prediction of Chronic Lung Allograft Dysfunction generated multiple fingerprints that enabled the development of predictors of CLAD. These results open the way to the integration of these fingerprints into a predictive handprint.

Biomarkers for Chronic Lung Allograft Dysfunction: Ready for Prime Time?

Chronic lung allograft dysfunction (CLAD) remains a major hurdle impairing lung transplant outcome. Parallel to the better clinical identification and characterization of CLAD and CLAD phenotypes, there is an increasing urge to find adequate biomarkers that could assist in the earlier detection and differential diagnosis of CLAD phenotypes, as well as disease prognostication. The current status and state-of-the-art of biomarker research in CLAD will be discussed with a particular focus on radiological biomarkers or biomarkers found in peripheral tissue, bronchoalveolar lavage' and circulating blood' in which significant progress has been made over the last years. Ultimately, although a growing number of biomarkers are currently being embedded in the follow-up of lung transplant patients, it is clear that one size does not fit all. The future of biomarker research probably lies in the rigorous combination of clinical information with findings in tissue, bronchoalveolar lavage' or blood. Only by doing so, the ultimate goal of biomarker research can be achieved, which is the earlier identification of CLAD before its clinical manifestation. This is desperately needed to improve the prognosis of patients with CLAD after lung transplantation.

Novel biomarkers of chronic lung allograft dysfunction: is there anything reliable?

PURPOSE OF REVIEW

Chronic lung allograft dysfunction (CLAD) remains a major barrier preventing long-term survival following lung transplantation. As our clinical knowledge regarding its definition and presentation has significantly improved over the last years, adequate biomarkers to predict development of CLAD, phenotype of CLAD or prognosis post-CLAD diagnosis are definitely needed.

RECENT FINDINGS

Radiological and physiological markers are gradually entering routine clinical practice. In-depth investigation of biological samples including broncho-alveolar lavage, biopsy and serum has generated potential biomarkers involved in fibrogenesis, airway injury and inflammation but none of these are universally accepted or implemented although progress has been made, specifically regarding donor-derived cell-free DNA and donor-specific antibodies.

SUMMARY

Although a lot of promising biomarkers have been put forward, a very limited number has made it to routine clinical practice. Nevertheless, a biomarker that leads to earlier detection or more adequate disease phenotyping would advance the field enormously.

Differences of Sleep Disorders Between Vestibular Migraine and Benign Paroxysmal Positional Vertigo

Introduction: Sleep disorders can affect the overall health and quality of life of patients. This study was conducted to compare the differences of sleep disorders in vestibular migraine (VM) patients and benign paroxysmal positional vertigo (BPPV) patients. Methods: VM patients, BPPV patients, and healthy controls (HCs) were recruited. Pittsburgh sleep quality index and polysomnography monitoring were used as subjective and objective, respectively, evaluation methods to evaluate the sleep quality of participants in the latest month. Results: Fifty-seven BPPV patients, 48 VM patients, and 42 HCs were included in this study. There were 79.16% VM patients, 54.39% BPPV patients, and 14.28% HCs with sleep disorders. The difference in the incidence rate of sleep disorders was significant between VM patients and BPPV patients (p = 0.008) and significantly higher in both the VM group (p < 0.00001) and BPPV group (p = 0.00004) than in the HC groups (14.28%). Compared with BPPV patients, the VM patients had the significantly lower sleep efficiency (p < 0.001) and N3 (p < 0.001) and the significantly higher time of wake-up after sleep onset (p < 0.001), N1 (p < 0.001), and N2 (p < 0.001). Meanwhile, the VM patients had significantly higher incidence rates of severe obstructive sleep apnea hypoventilation syndrome (p = 0.001) and periodic leg movement in sleep (p = 0.016). Conclusion: The incidence rate of sleep disorders was significantly higher in both VM and BPPV patients than in the HC groups. To improve the curative effects, clinicians should pay more attention to the comorbidity of sleep disorders in treating VM and BPPV.