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Radioulnar Synostosis-Hematology (RUS-H) Syndrome: Description of the New Syndrome and Comparison to Similar Syndromes

2012· article· en· W2560338088 on OpenAlexaboutno aff
Evangelista E Jessie, Mary Ruisi, Daniel J. Green, Rachel Burt, J. A. Davis, Regina A. Macatangay, Farid Boulad, Shivani Shah, Brenda Oiyemhonlan, Benjamin T. Kile, James B. Bussel

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePTPN11Noonan syndromeMacrocytic anemiaNeutropeniaLeukocytosisPediatricsHypoplasiaInternal medicineAnemiaDermatologyGastroenterologyCancer

Abstract

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Abstract Abstract 1100 Congenital radioulnar synostostis (RUS) is a rare anomaly characterized by fusion of the radius and ulna. RUS occurs more frequently in males than females, and is bilateral in 50% of cases. Since 1793, there have been > 400 cases reported. Literature review revealed 7 rare syndromes with RUS and hematologic problems including our newly named RUS-H Syndrome: 1) Diamond-Blackfan Anemia (DBA) associated with normochromic, macrocytic anemia in early infancy and erythroblastopenia; 2) Amegakaryocytic Thrombocytopenia Radioulnar Syndrome (ATRUS, HoxA11 mutation) with thrombocytopenia since birth requiring stem-cell transplantation; 3) IVIC Syndrome with mild thrombocytopenia and leukocytosis; 4) WT Syndrome involving a wide array of hematologic abnormalities including easy bruising, hypoplastic anemia, pancytopenia, Acute Lymphoblastic Leukemia (ALL), and Acute Myeloblastic Leukemia (AML); 5) Cohen Syndrome with neutropenia and fluctuating thrombocytopenia; 6) Noonan Syndrome with abnormal bleeding and easy bruising; and 7) RUS-H Syndrome (not involving HoxA11 mutations) associated with a spectrum of hematologic abnormalities including easy bruising, recurrent epistaxis, neutropenia, thrombocytopenia, ALL and aplastic anemia. This is a subsequent report to our ASH 2010 abstract. All 7 syndromes are associated with hand abnormalities. Six of the 7 syndromes (not Cohen) are associated with hearing loss/ear abnormalities. Four syndromes (DBA, ATRUS, WT, and RUS-H) have an increased risk of hematological malignancy. DBA, IVIC, Cohen, and Noonan have abnormalities of the eye and genitourinary system. DBA, WT, Cohen, and Noonan Syndromes are associated with dysmorphic facial features. ATRUS, IVIC, Cohen, and Noonan Syndromes all exhibit lower limb abnormalities. DBA, Cohen, Noonan, and RUS-H are associated with short stature. DBA, IVIC, Noonan, and RUS-H Syndromes are associated with kidney abnormalities and structural heart defects. Three Syndromes (DBA, IVIC, and Cohen) have cranial abnormalities. DBA IVIC, and Noonan Syndrome have structural defects of the shoulder. IVIC, Cohen, and Noonan Syndromes are associated with spinal anomalies. Two Syndromes (DBA and Noonan Syndrome) are associated with liver, spleen, and neck abnormalities. Cohen and Noonan Syndrome are associated with developmental delays. Lastly, WT and Noonan Syndrome are associated with skin abnormalities (Figure 1). This abstract highlights the association of RUS, other congenital abnormalities, and hematologic problems in previously described syndromes and in the novel RUS-H Syndrome. DBA, Cohen, and Noonan Syndrome are the most common of the 7 syndromes, with DBA estimated at 5 per 1,000,000; Cohen Syndrome predicted to have a prevalence of <1,000; and Noonan Syndrome predicted to have a prevalence of <1 in 2,500; however, RUS in DBA, Cohen, and Noonan Syndrome is limited to case reports. RUS-H Syndrome has been identified in 12 families in the United States, Canada, and England. IVIC and WT Syndromes have been reported in 4 families total, and ATRUS with an identified HoxA11 mutation has been reported in at least 2 families. Since RUS may often be missed on routine physical examination, we recommend specific evaluation of pronation/supination in patients with hematological problems of unknown etiology. Additionally, we recommend that a targeted genetic panel be developed to detect mutations that are known for syndromes involving RUS, blood abnormalities, and other similar orthopedic entities that have cross-over manifestations like Thrombocytopenia-Absent Radii (TAR) Syndrome. This panel might consist of mutations associated with DBA (RPL5, RPL11, RPL35A, RPS7, RPS10, RPS17, RPS19, RPS24, and RPS26 mutations), with ATRUS (HoxA11 mutation), with IVIC Syndrome (SALL4 mutations), with Cohen Syndrome (8q22.2q22.3/COH1 deletion), with Noonan Syndrome (PTPN11, SOS1, RAF1, KRAS, NRAS, and BRAF mutations) and with TAR Syndrome (RBM8A null allele and noncoding SNP). The causative mutations of WT and RUS-H Syndromes have yet to be discovered. Genetic analysis of 6 of the 12 families with RUS-H Syndrome did not reveal a HoxA11 mutation. Broader sequencing techniques are underway for all 12 families in our RUS-H cohort, with hopeful detection of a new candidate gene as the unifying causative factor for the abnormalities in limb formation and hematopoiesis. Disclosures: Bussel: Ligand: Membership on an entity's Board of Directors or advisory committees, Research Funding; Immunomedics: Research Funding; IgG of America: Research Funding; Genzyme: Research Funding; GlaxoSmithKline: Family owns GSK stock, Family owns GSK stock Other, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cangene: Research Funding; Amgen: Family owns Amgen stock Other, Membership on an entity's Board of Directors or advisory committees, Research Funding; Eisai: Membership on an entity's Board of Directors or advisory committees, Research Funding; Shionogi: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sysmex: Research Funding; Portola: Consultancy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
Admission routes1
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