Mono/polyclonal free light chains as challenging biomarkers for immunological abnormalities

Application of the Monoclonal Autoantibody and Its Target Protein Derived from the Peripheral Blood of SLE Patients in Serological Diagnosis and Differential Diagnosis of SLE

INTRODUCTION

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder with limited reliable diagnostic biomarkers. This study evaluates the utility of DEAD-box helicase 5 (DDX5) as a diagnostic and differential marker for SLE and assesses the performance of a capture bead-based flow cytometry (CBFCM) method for detecting serum proteins.

METHOD

Serum samples were collected from 52 patients with SLE, 38 patients with rheumatoid arthritis (RA), 49 patients with lung cancer (LC), and 50 healthy controls (HCs). Levels of DDX5, anti-DDX5, anti-dsDNA, and anti-Sm were quantified using enzyme-linked immunosorbent assay (ELISA) and CBFCM.

RESULTS

Serum DDX5 levels were significantly elevated in patients with SLE compared to patients with RA and HCs, correlating with the SLE activity. DDX5 demonstrated strong discriminatory power between SLE and RA. Combining DDX5, anti-dsDNA, and anti-Sm as biomarkers yielded an area under the curve (AUC) of 0.976 for SLE diagnosis. Decision curve analysis indicated a high clinical benefit from the combined biomarkers. The sensitivity and specificity of DDX5 were 66.11% and 88.89% for ELISA, and 72% and 91.3% for CBFCM.

DISCUSSION

DDX5 shows promise as a novel serological biomarker for SLE diagnosis and differential diagnosis. Additionally, CBFCM outperforms ELISA in detecting soluble serum proteins.

Serum-free light chains as a dependable biomarker for stratifying patients with metabolic dysfunction-associated steatotic liver disease

BACKGROUND AND AIMS

Adaptive immunity is gaining a significant role in progression of metabolic dysfunction-associated steatotic liver disease (MASLD). B-cell activity can be assessed by serum-free light chains (sFLCs) k and λ levels. The objective of the present investigation is to examine the utility of sFLCs as non-invasive biomarkers for the stratification of MASLD.

METHODS

We enrolled a consecutive cohort from an outpatient liver unit. Diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) was made with liver biopsy according to current guidelines. Compensated advanced chronic liver disease (cACLD) and clinically significant portal hypertension (CSPH) were defined according to Baveno VII criteria. sFLCs were measured by turbidimetry using an immunoassay.

RESULTS

We evaluated 254 patients, 162/254 (63.8%) were male. Median age was 54 years old, and the median body mass index was 28.4 kg/m2. A total of 157/254 (61.8%) subjects underwent liver biopsy: 88 had histological diagnosis of MASH, 89 were considered as simple metabolic dysfunction-associated steatotic liver (MASL) and 77/254 (30.3%) patients with compensated metabolic dysfunction-associated cirrhosis. By using Baveno VII criteria, 101/254 (39.7%) patients had cACLD; among them, 45/101 (44.5%) had CSPH. Patients with cACLD showed higher sFLC levels compared with patients without cACLD (p < .01), and patients with CSPH showed higher sFLC levels than patients without CSPH (p < .01). At multivariable analysis, sFLCs were associated with cACLD (p < .05) independently from γ-globulins and other known dysmetabolic risk factors. κFLC was associated with CSPH (p < .05) independently from γ-globulins and other known dysmetabolic risk factors.

CONCLUSION

sFLCs could be a simple biomarker for stratification of cACLD in MASLD patients.

Immunoglobulin free light chains in severe asthma patient: Could they be a new biomarker?

BACKGROUND

Increasing evidence is available about the presence of increased serum concentration of immunoglobulin (Ig) free light chains (FLCs) in both atopic and non-atopic inflammatory diseases, including severe asthma, providing a possible new biomarker of disease.

METHODS

We analyzed clinical and laboratory data, including FLCs, obtained from a cohort of 79 asthmatic subjects, clinically classified into different GINA steps. A control group of 40 age-matched healthy donors (HD) was considered. Particularly, HD have been selected according to the absence of monoclonal components (in order to exclude paraproteinemias), were tested for total IgE (that were in the normal ranges) and were negative for aeroallergens specific IgE. Moreover, no abnormality of common inflammatory markers (i.e., erythrocyte sedimentation rate and C-reactive protein) was detectable.

RESULTS

FLC-k levels were significantly increased in the asthmatic population, compared to the control group. Despite the absence of statistically significant differences in FLC-λ levels, the FLC-k/FLC-λ ratio displayed remarkable differences between the two groups. A positive correlation between FLC-κ and FLC-λ levels was found. FLC- λ level displayed a significant negative correlation with the FEV1 value. Moreover, the FLC-κ /FLC- λ ratio was negatively correlated with the SNOT-22 score and a positive correlation was observed between FLCs and Staphylococcus Aureus IgE enterotoxins sensitization.

CONCLUSIONS

Our findings confirmed the role of FLCs in asthma as a potential biomarker in an inflammatory disease characterized by different endotypes and phenotypes. In particular, FLC-κ and FLC-k/FLC-λ ratio could be a qualitative indicator for asthma, while FLC-λ levels could be a quantitative indicator for clinical severity parameters.

Molecular and immune signatures, and pathological trajectories of fatal COVID-19 lungs defined by in situ spatial single-cell transcriptome analysis

Despite intensive studies during the last 3 years, the pathology and underlying molecular mechanism of coronavirus disease 2019 (COVID-19) remain poorly defined. In this study, we investigated the spatial single-cell molecular and cellular features of postmortem COVID-19 lung tissues using in situ sequencing (ISS). We detected 10 414 863 transcripts of 221 genes in whole-slide tissues and segmented them into 1 719 459 cells that were mapped to 18 major parenchymal and immune cell types, all of which were infected by SARS-CoV-2. Compared with the non-COVID-19 control, COVID-19 lungs exhibited reduced alveolar cells (ACs) and increased innate and adaptive immune cells. We also identified 19 differentially expressed genes in both infected and uninfected cells across the tissues, which reflected the altered cellular compositions. Spatial analysis of local infection rates revealed regions with high infection rates that were correlated with high cell densities (HIHD). The HIHD regions expressed high levels of SARS-CoV-2 entry-related factors including ACE2, FURIN, TMPRSS2 and NRP1, and co-localized with organizing pneumonia (OP) and lymphocytic and immune infiltration, which exhibited increased ACs and fibroblasts but decreased vascular endothelial cells and epithelial cells, mirroring the tissue damage and wound healing processes. Sparse nonnegative matrix factorization (SNMF) analysis of niche features identified seven signatures that captured structure and immune niches in COVID-19 tissues. Trajectory inference based on immune niche signatures defined two pathological routes. Trajectory A primarily progressed with increased NK cells and granulocytes, likely reflecting the complication of microbial infections. Trajectory B was marked by increased HIHD and OP, possibly accounting for the increased immune infiltration. The OP regions were marked by high numbers of fibroblasts expressing extremely high levels of COL1A1 and COL1A2. Examination of single-cell RNA-seq data (scRNA-seq) from COVID-19 lung tissues and idiopathic pulmonary fibrosis (IPF) identified similar cell populations consisting mainly of myofibroblasts. Immunofluorescence staining revealed the activation of IL6-STAT3 and TGF-β-SMAD2/3 pathways in these cells, likely mediating the upregulation of COL1A1 and COL1A2 and excessive fibrosis in the lung tissues. Together, this study provides a spatial single-cell atlas of cellular and molecular signatures of fatal COVID-19 lungs, which reveals the complex spatial cellular heterogeneity, organization, and interactions that characterized the COVID-19 lung pathology.

The Use of Kappa Free Light Chains to Diagnose Multiple Sclerosis

Background: The positive implications of using free light chains in diagnosing multiple sclerosis have increasingly gained considerable interest in medical research and the scientific community. It is often presumed that free light chains, particularly kappa and lambda free light chains, are of practical use and are associated with a higher probability of obtaining positive results compared to oligoclonal bands. The primary purpose of the current paper was to conduct a systematic review to assess the up-to-date methods for diagnosing multiple sclerosis using kappa and lambda free light chains. Method: An organized literature search was performed across four electronic sources, including Google Scholar, Web of Science, Embase, and MEDLINE. The sources analyzed in this systematic review and meta-analysis comprise randomized clinical trials, prospective cohort studies, retrospective studies, controlled clinical trials, and systematic reviews. Results: The review contains 116 reports that includes 1204 participants. The final selection includes a vast array of preexisting literature concerning the study topic: 35 randomized clinical trials, 21 prospective cohort studies, 19 retrospective studies, 22 controlled clinical trials, and 13 systematic reviews. Discussion: The incorporated literature sources provided integral insights into the benefits of free light chain diagnostics for multiple sclerosis. It was also evident that the use of free light chains in the diagnosis of clinically isolated syndrome (CIS) and multiple sclerosis is relatively fast and inexpensive in comparison to other conventional state-of-the-art diagnostic methods, e.g., using oligoclonal bands (OCBs).