The Use of Recombinant DNA Techniques for the Diagnosis of Familial Hypercholesterolaemia

  • S. Humphries
  • R. Taylor
  • M. Jeenah
  • M. Seed

Summary

In the UK, about 5% of patients with familial hypercholesterolaemia have a detectable deletion or rearrangement of part of the LDL-receptor gene. This results in the detection of shorter or abnormal sized fragments of the LDL-receptor gene in a Southern blot hybridization. This can be used to follow the inheritance of the defective gene, and for diagnosis in the families of these individuals. In the families of the rest of the patients, diagnosis may be possible using linked restriction fragment length polymorphisms (RFLPs) detected with the LDL-receptor probe. There are now ten common RFLPs of the LDL-receptor gene, with variable sites in the 3′ half of the gene. Over 80% of patients are heterozygous for at least one of these RFLPs, and therefore potentially informative for DNA diagnosis. For a foetus at risk of homozygous familial hypercholesterolaemia, antenatal diagnosis may also be possible using these methods. However, family studies require samples to be available from affected or unaffected relatives of the patient, and this limits the applicability of the tests. For some mutations, the base pair change causing the defect in the LDL-receptor itself creates or destroys a site for a restriction enzyme. Such ‘mutation-specific’ RFLPs could be used for population screening, but so far have only been reported for the familial hypercholesterolaemia mutation that is common in Lebanon. In the future it may be possible to develop mutation-specific oligonucleotide probes for the diagnosis of familial hypercholesterolaemia. These would be appropriate for population screening or screening patients with hyperlipidaemia. This information may be useful if different mutations require different therapeutic strategies.

Keywords

Familial Hypercholesterolaemia Restriction Fragment Length Polymorphism Defective Gene Lipid Research Clinic Program Pvuii Polymorphism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1988

Authors and Affiliations

  • S. Humphries
    • 1
  • R. Taylor
    • 1
  • M. Jeenah
    • 1
  • M. Seed
    • 2
  1. 1.Charing Cross Sunley Research CentreLondonUK
  2. 2.Charing Cross Hospital Medical SchoolLondonUK

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