{"doi":"10.1002/ajh.27669","title":"Identifying Microbiota and Immune Host Factors Associated With Bleeding Risk in Children With Immune Thrombocytopenia","abstract":"The hallmark of immune thrombocytopenia (ITP) is a decrease in the number of platelets in the blood, leading to excessive bruising and bleeding. While most clinically significant bleeding events in ITP occur at platelet counts < 30,000/uL, patients with comparable platelet counts may have variable bleeding phenotypes. Inflammation has been shown to promote thrombosis through increasing pro-coagulant factors and inhibiting anticoagulant pathways. The gut microbiome is critical in host immune system education and thrombotic pathways, but its role in bleeding risk in ITP has not been studied. For example, lipopolysaccharide (LPS), the outer membrane glycoprotein found in gram-negative bacteria, increases coagulability by activating the toll-like receptor-4 (TLR4)-induced coagulation pathway [1]. In contrast, the gut microbiota-derived metabolite butyrate induces immune tolerance, mitigates inflammation, and minimizes LPS translocation in the intestines [1]. Systemic cytokine production correlates with specific gut microbiota, as evidenced by lower TNF- levels in humans with high levels of Bifidobacterium adolescentis bacteria [1]. We aimed to investigate the role of the microbiome and cytokine production in ITP patients with mild versus moderate–severe bleeding phenotype. We hypothesized that children with ITP with a moderate–severe bleeding phenotype would have increased levels of gut microbiota associated with mitigating local and systemic inflammation and increased anti-inflammatory systemic cytokines, as inflammation has been shown to promote thrombosis. Our prospective IRB-approved cohort study included patients < 18 years of age with acute ITP within 3 months of diagnosis and with platelet counts ≤ 30,000/uL at diagnosis at the University of Texas Southwestern (UTSW) Medical Center and Children's Health. Fecal and blood samples were obtained in inpatient and outpatient settings and stored de-identified with study-specific sample IDs. Stool samples were obtained within 36 h of inpatient IVIG or steroid initiation and prior to outpatient steroid treatment. 16S rRNA genes (variable region 4, V4) were amplified, sequenced, and analyzed from each sample. Alpha diversity metrics (Simpson diversity, Shannon diversity, Chao1 and Faith richness) were calculated. Output matrices were further analyzed by principal coordinate analysis (PCoA) using weighted UniFrac and Bray–Curtis, along with linear discriminant analysis (LDA) effect size (LEfSe) to identify differences in relative abundance at taxonomic levels. Blood samples were loaded into the MAGPIX system (Luminex corporation, Austin, Texas, USA) for cytokine analysis in the UTSW Genomics and Microarray Core Facility. We assigned study participants to two groups, mild or moderate–severe, using the Buchanan-Adix bleeding score, with mild participants having a score ≤ 3a and moderate–severe a score ≥ 3b [2]. Score cutoffs were decided based on the most recent American Society of Hematology guidelines for the treatment of ITP [2]. Sample sizes for blood and stool samples were estimated based on previous research comparing cytokine and microbiota data between healthy controls and ITP participants to achieve a power of 80% [3, 4]. Clinical information obtained includes age, gender, ethnicity, antibiotic use within 1 month of diagnosis, ITP treatment, preceding viral infection, history of autoimmune disease, and bleed location. Thirty-eight patients with ITP were evaluated for inclusion in this study. Eight patients were excluded, two of whom had past oncologic diagnoses, one with ITP > 6 months past diagnosis; five refused to participate. Thirty participants with a median age of 5.5 years (IQR 2–9.5) were included, and blood samples were collected from each participant. 11 (36.7%) were diagnosed with mild phenotype and 19 (63%) with moderate–severe phenotype. The median platelet count in the moderate–severe group was 4 (IQR 4–6), and 6 (IQR 4–15) in the mild group (p = 0.32, Table S1). ","journal":"American Journal of Hematology","year":2025,"id":543467,"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":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9558,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1146894,"name":"Parastoo Sabaeifard","orcid":"0000-0002-1057-5858","position":1,"is_corresponding":false},{"id":493602,"name":"Laura Coughlin","orcid":"0000-0003-1588-733X","position":2,"is_corresponding":false},{"id":475206,"name":"Nicole Poulides","orcid":"0000-0002-1746-7673","position":3,"is_corresponding":false},{"id":1018359,"name":"Shuheng Gan","orcid":"0000-0002-1790-6656","position":4,"is_corresponding":false},{"id":14650,"name":"Xiaowei Zhan","orcid":"0000-0002-6249-7193","position":5,"is_corresponding":false},{"id":1249735,"name":"Mary Dang","orcid":"0000-0003-0187-4335","position":6,"is_corresponding":false},{"id":237268,"name":"Andrew Y. Koh","orcid":"0000-0003-2172-5126","position":7,"is_corresponding":false},{"id":298689,"name":"Ayesha Zia","orcid":"0000-0003-3283-0415","position":8,"is_corresponding":false},{"id":1342987,"name":"Shelly Saini","orcid":null,"position":0,"is_corresponding":true}],"reference_count":6,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:53:04.088079Z","pmid":"40110651","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":[]}