Monocyte/macrophages may exert prominent roles in macrophage activation syndrome

Secondary Hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening complication mostly occurs in adult patients with rheumatic disease, infection or lymphoma. To adequately steer treatment, clear discrimination of sHLH entities is essential. We aimed to discriminate serum biomarkers which can separate MAS from EBV associated HLH (EBV-HLH) and Lymphoma associated HLH (L-HLH) adequately. Samples from patients aged > 15 diagnosed with sHLH were analyzed using Luminex Multiple Assays (34-plex for pre-2022; 11-plex for post-2022). 209 patients were divided into three cohorts due to change of Luminex kits. Among 86 patients enrolled pre-2021, 45 patients enrolled in 2021-2022, and 78 patients enrolled post-2022. Clinical data and serum biomarkers were analyzed among MAS, EBV-HLH and L-HLH in three cohorts by Kruskal-Wallis Analysis (K-W). The Heatmap and Principal Component Analysis (PCA) were used to describe the distinctive expression of serum biomarkers in MAS, EBV-HLH and L-HLH. Other than the relationship between clinical data and biomarkers was exhibited in the Heatmap according to the Spearman's Rank Co-efficient. Furthermore Network analysis recognized the prominent biomarker in MAS. The blooding cells disproportion declined in MAS patients relative to EBV-HLH and L-HLH. Other than the level of sCD25 increased higher in EBV-HLH and L-HLH patients than MAS patients. Progressive levels of MIP-1α and IL-10 were elevated in patients with EBV-HLH and L-HLH relative to MAS. PCA and the heatmap of serum biomarkers expressions did not discriminate MAS from EBV-HLH and L-HLH efficiently. Although there was no significant difference in the relationship between clinical data and serum biomarkers, we observed the further positive association between myeloid and lymphoid-derived serum biomarkers in MAS compared with EBV-HLH and L-HLH. Further analysis revealed that IL-17 was as a prominent biomarker in pathology in MAS by Network Analysis. (1) The relationship between myeloid and lymphoid-derived biomarkers was further relevant in MAS than EBV-HLH and L-HLH. (2) The IL-17 released mostly by Th-17 cells was grouped together closely with other inflammatory mediators and we infer that IL-17 may exert an important role in MAS. These findings could guidance the efficacy of drugs targeting key cell and biomarkers specifically associated with MAS.

Authors

Institutions

Publication Details

Journal
Annals of Hematology
Published
2025-11-07
DOI
https://doi.org/10.1007/s00277-025-06640-3
Primary Topic
Autoimmune and Inflammatory Disorders Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Monocyte/macrophages may exert prominent roles in macrophage activation syndrome

Jingshi Wang, Zhao Wang, Dongfei Yin
Annals of Hematology
Autoimmune and Inflammatory Disorders Research
article

Monocyte/macrophages may exert prominent roles in macrophage activation syndrome

Jingshi Wang, Zhao Wang, Dongfei Yin
article en

Abstract

Secondary Hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening complication mostly occurs in adult patients with rheumatic disease, infection or lymphoma. To adequately steer treatment, clear discrimination of sHLH entities is essential. We aimed to discriminate serum biomarkers which can separate MAS from EBV associated HLH (EBV-HLH) and Lymphoma associated HLH (L-HLH) adequately. Samples from patients aged > 15 diagnosed with sHLH were analyzed using Luminex Multiple Assays (34-plex for pre-2022; 11-plex for post-2022). 209 patients were divided into three cohorts due to change of Luminex kits. Among 86 patients enrolled pre-2021, 45 patients enrolled in 2021-2022, and 78 patients enrolled post-2022. Clinical data and serum biomarkers were analyzed among MAS, EBV-HLH and L-HLH in three cohorts by Kruskal-Wallis Analysis (K-W). The Heatmap and Principal Component Analysis (PCA) were used to describe the distinctive expression of serum biomarkers in MAS, EBV-HLH and L-HLH. Other than the relationship between clinical data and biomarkers was exhibited in the Heatmap according to the Spearman's Rank Co-efficient. Furthermore Network analysis recognized the prominent biomarker in MAS. The blooding cells disproportion declined in MAS patients relative to EBV-HLH and L-HLH. Other than the level of sCD25 increased higher in EBV-HLH and L-HLH patients than MAS patients. Progressive levels of MIP-1α and IL-10 were elevated in patients with EBV-HLH and L-HLH relative to MAS. PCA and the heatmap of serum biomarkers expressions did not discriminate MAS from EBV-HLH and L-HLH efficiently. Although there was no significant difference in the relationship between clinical data and serum biomarkers, we observed the further positive association between myeloid and lymphoid-derived serum biomarkers in MAS compared with EBV-HLH and L-HLH. Further analysis revealed that IL-17 was as a prominent biomarker in pathology in MAS by Network Analysis. (1) The relationship between myeloid and lymphoid-derived biomarkers was further relevant in MAS than EBV-HLH and L-HLH. (2) The IL-17 released mostly by Th-17 cells was grouped together closely with other inflammatory mediators and we infer that IL-17 may exert an important role in MAS. These findings could guidance the efficacy of drugs targeting key cell and biomarkers specifically associated with MAS.

Annals of HematologyVol. 104(11)
Capital Medical University (CN), Beijing Friendship Hospital (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 56%
Autoimmune and Inflammatory Disorders Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.