Congenital dyserythropoietic anemia type I: Updated report from the congenital dyserythropoietic anemia registry of North America
Bibliographic record
Abstract
Abstract Background Congenital dyserythropoietic anemias (CDA) are rare genetic disorders characterized by ineffective erythropoiesis and iron overload. The CDA Registry (CDAR) of North America aims to study the natural history and molecular pathogenesis of CDA. CDA-I is caused by biallelic variants in CDAN1 or CDIN1. Pegylated Interferon-α (PEG-IFN-α) is a promising treatment for CDA-I. Methods Patients with phenotypic or genetic diagnosis of CDA were enrolled with informed consent. Genetic work-up was offered, if not previously done. Clinical data were collected from patients and treating physicians. This study provides an update on the clinical courses of patients with CDA-I in CDAR. Results Nineteen CDAR participants have been diagnosed with CDA-I (median age 11.4; range 0.75 to 35 yrs). The median age at diagnosis was 4.9 yrs (range: 0–27), including one prenatal diagnosis in a sibling of a known patient. Most patients presented at birth with neonatal anemia and jaundice requiring transfusions and phototherapy. Thirteen patients required transfusions in the neonatal period, 2 required intrauterine transfusions, 2 started transfusions between the ages of 5-6 months, and 2 never received a transfusion. One patient with transfusion-dependent anemia and intolerance to IFN-α and iron chelation died at age 23 yrs. Their course was complicated by other comorbidities including gastroparesis and malabsorption, requiring gastro-jejunal feeding. Thirteen patients (72%) are not currently receiving transfusions. Among these, 5 have been treated with PEG-IFN-α. Two achieved transfusion independence within one month of starting PEG-IFN-α and remain on weekly dosage with normalized hemoglobin (Hb) values and well-controlled liver iron content (LIC at 1.4, 1.7 mg/g) without chelation (previous peaks: 4.6, 10.1 mg/g). The first of these two patients was started on 80 mcg weekly at the age of 6 yrs, her dose was decreased after 4 yrs to 60 mcg weekly, since Hb was stable at ~12 g/dL. The second was started on a small dose of 18 mcg weekly at the age of 11 yrs and had a great response with Hb rising from 7-7.5 g/dL to >12 g/dL within 2 months. He remained stable on the same dose for 4 yrs, and the dose was increased recently to 28 mcg based on a downtrend in Hb along with the patient growing and gaining weight. One 11-yr-old patient maintained a Hb ~ 9 off transfusions since the age of ~ 6 months, was started on 90 mcg weekly with an improvement in Hb to 14 after 4 months on PEG-IFN-α. One patient with baseline Hb of 7 g/dL without transfusions, started PEG-IFN-α recently and continues dose titration. This patient has iron overload requiring chelation disproportionate to their history of transfusions, due to ineffective erythropoiesis. One patient became transfusion-independent after receiving PEG-IFN-α between ages 1-3 yrs and remains so at age 12 yrs. Of the remaining 8 patients, 6 had their anemia spontaneously improve between the ages of 3-13 months. One requires chelation due to iron overload although they are off transfusions since infancy (peak LIC: 6.5 mg/g). Five patients (28%) remain transfusion-dependent, a 3-yr, 5-yr, and 7-yr-old, and two adults (25 and 35 yrs) due to medication access, family or personal preferences; all five are treated with iron chelators. Of note, the 35-yr-old was initially misdiagnosed with hereditary spherocytosis and underwent splenectomy at 11 yrs of age. He was lost to follow up and represented in adulthood with hemolytic anemia and pulmonary hypertension. He has been on transfusions since then, achieving resolution of severe iron overload after approximately 6 yrs on two iron chelators. Conclusion Genetic testing is essential for accurate and timely CDA-I diagnosis. The natural history of CDA-I is variable. While 50% of patients experienced spontaneous anemia improvement, others rely on transfusions, or treatment with PEG-IFN-α. Most patients treated with PEG-IFN-α achieved transfusion independence and maintained stable LIC without chelation, although the time and dose needed vary. Iron overload is a common complication and can develop spontaneously independent of blood transfusions. IFN-α treatment has improved iron overload in two of the patients without concurrent use of iron chelation, likely by improving ineffective erythropoiesis and iron utilization. Further research is needed to understand its mechanism of action and address barriers to treatment initiation and optimization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".