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Hemophilia B: molecular pathogenesis and mutation analysis
Author(s) -
Goodeve A. C.
Publication year - 2015
Publication title -
journal of thrombosis and haemostasis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.947
H-Index - 178
eISSN - 1538-7836
pISSN - 1538-7933
DOI - 10.1111/jth.12958
Subject(s) - missense mutation , sanger sequencing , haemophilia b , genetics , factor ix , nonsense mutation , mutation , biology , haemophilia a , medicine , gene , haemophilia
Summary Hemophilia B is an X‐chromosome‐linked inherited bleeding disorder primarily affecting males, but those carrier females with reduced factor IX activity ( FIX :C) levels may also experience some bleeding. Genetic analysis has been undertaken for hemophilia B since the mid‐1980s, through linkage analysis to track inheritance of an affected allele, and to enable determination of the familial mutation. Mutation analysis using PCR and Sanger sequencing along with dosage analysis for detection of large deletions/duplications enables mutation detection in > 97% of patients with hemophilia B. The risk of the development of inhibitory antibodies, which are reported in ~ 2% of patients with hemophilia B, can be predicted, especially in patients with large deletions, and these individuals are also at risk of anaphylaxis, and nephrotic syndrome if they receive immune tolerance induction. Inhibitors also occur in patients with nonsense mutations, occasionally in patients with small insertions/deletions or splice mutations, and rarely in patients with missense mutations (p.Gln237Lys and p.Gln241His). Hemophilia B results from several different mechanisms, and those associated with hemophilia B Leyden, ribosome readthrough of nonsense mutations and apparently ‘silent’ changes that do not alter amino acid coding are explored. Large databases of genetic variants in healthy individuals and patients with a range of disorders, including hemophilia B, are yielding useful information on sequence variant frequency to help establish possible variant pathogenicity, and a growing range of algorithms are available to help predict pathogenicity for previously unreported variants.