{"doi":"10.1002/ajh.26528","title":"Clinical characteristics of cytomegalovirus‐positive pediatric acute lymphoblastic leukemia at diagnosis","abstract":"Infections and antigenic exposures during childhood are associated with pediatric acute lymphoblastic leukemia (ALL) and are thought to lead to immune dysregulation stimulating pre-leukemic clones to expand and progress to overt leukemia.1 Emerging epidemiologic and laboratory evidence suggests cytomegalovirus (CMV) may contribute to the development of childhood ALL,2, 3 inspiring further investigative efforts and for the first time, identifying a specific target for ALL prevention. In this study, we aimed to better elucidate the role of CMV in ALL etiology by screening diagnostic leukemia bone marrow samples for CMV DNA using a highly quantitative droplet digital PCR (ddPCR) assay. We identified differences in demographic features and leukemia subtypes between CMV-positive and CMV-negative cases, supporting the hypothesis that CMV plays a role in ALL development. Diagnostic leukemia bone marrow samples were obtained from the California Childhood Leukemia Study (CCLS), which included children less than 15 years old with newly diagnosed leukemia. The QIAamp DNA Blood Mini Kit (Qiagen) was used to isolate DNA from 5 mL bone marrow aspirate samples acquired from 1078 patients. A ddPCR assay was used to screen samples for CMV DNA targeting a sequence recurrently identified in samples that had previously undergone whole genome sequencing. To normalize the CMV-positive droplet count to the amount of DNA in the reaction, a second ddPCR reaction was run on all samples to detect single copy human DNA target. A ratio of CMV to human haploid positive droplets (CMV-ratio) was calculated as a measure of the level of CMV-positivity. Additional methods are included in Supporting information. Both ALL and acute myeloid leukemia (AML) cases were included in the analysis with AML serving as a control as it represents a similarly immunocompromised state as ALL cases, but less frequently exhibits CMV DNA.2 Samples were classified as CMV-positive if the CMV-ratio was greater than 0 and CMV-negative if equal to 0. CMV-ratio was also categorized into quintiles or tertiles based on the distribution in the overall cohort with a CMV-ratio of 0 as the referent for analyses of associations with CMV viral DNA load. Clinical and demographic features were compared between the CMV-positive and CMV-negative cases including leukemia phenotype, age at diagnosis, sex, race, and ethnicity. Using existing data for ALL cases, we assessed the distribution of somatic gene deletions (n = 702), RAS mutations (n = 469), and FLT3 alterations (n = 206) between CMV-positive and CMV-negative groups. Differential gene expression was performed using available Affymetrix Array gene expression data (n = 61) to compare CMV-positive ALL cases with high viral load to CMV-negative cases. SNP array data and ALL polygenic risk scores (PRS) were available for 435 ALL cases. The PRS and risk alleles for individual SNPs were compared between CMV-positive and CMV-negative groups. Genetic ancestry (Latino and non-Latino) determined from the SNP data was included in this analysis. Wilcoxon rank sum (continuous variables) and chi-square tests (categorical variables) were used for univariate analyses and logistic regression for multivariable analysis. All statistical tests were two-sided and results were considered statistically significant for p < .05. Differential gene expression analysis was performed using logistic regression for individual genes and gene ontology analysis was performed using the software IPA (QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis). A total of 743 ALL samples and 125 AML samples were included in the analysis. Of these, 49% (n = 424) were CMV-positive and 51% (n = 444) were CMV-negative. Age, sex, race, and ethnicity were compared by CMV status in the overall group and separately among ALL and AML cases (Table S1). Among ALL cases, CMV-positive children were older than their CMV-negative counterparts (median age at diagnosis","journal":"American Journal of Hematology","year":2022,"id":275039,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9619,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":930598,"name":"Katti Arroyo","orcid":"0000-0001-7938-573X","position":1,"is_corresponding":false},{"id":107662,"name":"Paige M. Bracci","orcid":"0000-0001-9338-9307","position":2,"is_corresponding":false},{"id":653515,"name":"Shaobo Li","orcid":"0000-0002-0544-5338","position":3,"is_corresponding":false},{"id":441131,"name":"Catherine Metayer","orcid":null,"position":4,"is_corresponding":false},{"id":29973,"name":"Scott C. Kogan","orcid":"0000-0002-2395-8479","position":5,"is_corresponding":false},{"id":268237,"name":"George A. Wendt","orcid":"0000-0003-3608-9601","position":6,"is_corresponding":false},{"id":268235,"name":"Stephen Francis","orcid":"0000-0002-6488-6272","position":7,"is_corresponding":false},{"id":107666,"name":"Adam J. de Smith","orcid":"0000-0003-4880-7543","position":8,"is_corresponding":false},{"id":409685,"name":"Joseph L. Wiemels","orcid":"0000-0003-4838-9951","position":9,"is_corresponding":false},{"id":924989,"name":"Rachel Gallant","orcid":"0000-0003-0860-7184","position":0,"is_corresponding":true}],"reference_count":6,"raw_metadata":null,"created_at":"2026-07-19T00:28:16.928746Z","pmid":"35285969","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":[]}