{"doi":"10.1016/j.bbih.2025.101089","title":"Biomarker-based profiling of fatigue in childhood cancer survivors: evidence for distinct inflammatory and glial-associated profiles","abstract":null,"journal":"Brain, Behavior, &amp; Immunity - Health","year":2025,"id":648375,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":2,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1689688,"name":"Sabine Verschueren","orcid":null,"position":1,"is_corresponding":false},{"id":1689689,"name":"Lize Van Meerbeeck","orcid":null,"position":2,"is_corresponding":false},{"id":851203,"name":"Jurgen Lemiere","orcid":"0000-0002-1575-0889","position":3,"is_corresponding":false},{"id":1689694,"name":"Stephanie Humblet-Baron","orcid":null,"position":4,"is_corresponding":false},{"id":1689697,"name":"Charlotte Sleurs","orcid":"0000-0002-4480-8330","position":5,"is_corresponding":false},{"id":525348,"name":"Anne Uyttebroeck","orcid":"0000-0001-5644-424X","position":6,"is_corresponding":false},{"id":1689686,"name":"Deveny Vanrusselt","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Biomarker-based profiling of fatigue in childhood cancer survivors: evidence for distinct inflammatory and glial-associated profiles","abstract":"Background: Fatigue is a prevalent and burdensome late effect in childhood cancer survivors (CCS), yet its biological underpinnings remain poorly understood. This study examined associations between fatigue and blood-based biomarkers in CCS compared to healthy controls (HCs) and explored whether biologically distinct CCS profiles with respect to fatigue could be identified. Procedure: Eighty CCS (aged 14-28) and 35 age- and sex-matched HCs provided blood samples and completed the Pediatric Quality of Life Inventory Multidimensional Fatigue Scale (PedsQL-MFS). Plasma concentrations of 12 biomarkers (e.g., IL-2, TNF-α, BDNF, Total Tau, NfL, MCP-1, GFAP) were quantified using Meso Scale Discovery immunoassays. Analyses included group comparisons, Spearman correlations, and unsupervised clustering (hierarchical and k-means). Results: CCS reported significantly higher fatigue than HCs and showed significantly elevated levels of GFAP (d = 0.43), MCP-1 (d = 0.74), and Total Tau (d = 0.54). No individual biomarkers differentiated fatigued from non-fatigued CCS. Clustering revealed two biomarker-based CCS subgroups: one with high levels of inflammatory and neurodegenerative markers, and one with lower levels, yet fatigue severity was comparable. Within-cluster analyses showed distinct patterns: in the low-biomarker group, fatigue was associated with GFAP (ρ = -0.26 and ρ = -0.27, p < 0.05), whereas in the high-biomarker group, fatigue was more consistently linked to IL-8, IL-1α, and TNF-α (ρ = -0.38 to -0.49, p < 0.05). Conclusion: Findings suggest that fatigue in CCS may be associated with distinct biological pathways, including astrocyte-linked processes in one subgroup and systemic inflammation in another. This suggests the need for more personalized, biomarker-informed strategies to understand and manage fatigue in pediatric cancer survivorship.","is_dataset_classified":null,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"40838185","pmcid":"PMC12362137","openalex_id":"https://openalex.org/W4413142487","authors":[],"funders":[],"total_grants":0,"fwci":4.324,"citation_percentile":0.93704246,"influential_citations":0,"citation_trend":[{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1016/j.bbih.2025.101089","host_type":"journal"},{"url":"https://doi.org/10.1016/j.bbih.2025.101089","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S2666354625001474?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S2666354625001474?httpAccept=text/plain","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/40838185","host_type":"repository"},{"url":"https://research.tilburguniversity.edu/en/publications/fe5545fe-6520-41d7-ad61-4cc520682632","host_type":"repository"},{"url":"https://lirias.kuleuven.be/handle/20.500.12942/772757","host_type":"repository"},{"url":"https://doaj.org/article/07b188f1803443229dfd135a649e9466","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12362137","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC12362137","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC12362137?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Childhood Cancer Survivors' Quality of Life","Cancer survivorship and care","Fibromyalgia and Chronic Fatigue Syndrome Research"],"mesh_terms":[],"keywords":["Profiling (computer programming)","Biomarker","Childhood cancer","Medicine","Oncology","Biology","Bioinformatics","Computational biology","Cancer","Internal medicine","Genetics","Computer science","Biomarkers","Fatigue","Systemic Inflammation","Childhood Cancer Survivors","Astrocytic Processes","Fatigue Profiles"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T02:32:59.342786Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}