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Record W4409786199 · doi:10.70962/cis2025abstract.245

Expanding the Landscape of Inborn Errors of Immunity in Hematological Disorders: A Prospective Study on Hidden IEI and IEI Phenocopies

2025· article· en· W4409786199 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Human Immunity · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPhenocopyMedicineImmunityProspective cohort studyPediatricsImmunologyIntensive care medicineBiologyInternal medicineImmune systemGenetics

Abstract

fetched live from OpenAlex

Background Inborn errors of immunity (IEI) are increasingly associated not only with recurrent infections but also with hematological complications. The discovery of somatic mutations leading to “IEI phenocopies” has expanded the genetic understanding of these disorders. However, the clinical and genetic scope of IEI in hematological disorders remains underexplored in large-scale studies. Methods This study recruits patients under 25 years old with hematological abnormalities, categorized into four subgroups: autoimmune cytopenias (AICs), polyclonal lymphoproliferation (PL), monoclonal lymphoproliferation (ML), and bone marrow failure/myelodysplasia (BMF/MDS). Participants undergo immunological evaluations, including immunophenotyping, cytokine profiling, and autoantibody assays. Next-generation sequencing (NGS) is used to identify germline and somatic variants, with bulk RNA sequencing applied to validate variants and explore pathways in inconclusive cases. Additionally, this study aims to establish a dedicated consortium for the comprehensive study of IEI-related hematological disorders, bringing together multiple centers to collaborate on data collection and analysis. Patient advocacy organizations (PAOs) are involved to raise awareness and support participants. Results Retrospective data from Meyer Children’s Hospital IRCCS in Florence (2020–2024) showed feasibility, identifying 71 eligible patients: 38 with AICs, 15 with PL, 20 with lymphoma, and 12 with BMF/MDS. A similar number of patients are expected to enroll at this site over three years, with collaborating referral centers projected to recruit approximately 680 participants in total. Preliminary results from the initial 71 participants show a 35% detection rate of hidden IEI, supporting the study's premise. Conclusions This research is poised to enhance the understanding of IEI and IEI phenocopies in hematological disorders, revealing novel genetic contributors and biomarkers. The findings could lead to earlier diagnoses, personalized therapies, and more timely hematopoietic stem cell transplantation. Collaboration with PAOs will improve patient education, treatment adherence, and overall outcomes, while reducing healthcare burdens. This study represents a significant advancement in addressing the unmet needs of patients with hematological complications of IEI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.289
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it