Application of next generation sequencing to aid in effective diagnosis of familial hypercholesterolaemia

  • Satishkumar Krishnan

    Student thesis: Doctoral Thesis

    Abstract

    Familial Hypercholesterolaemia (FH) is an autosomal dominant inherited condition characterised by increased blood cholesterol levels which leads to xanthomas and coronary heart disease. Prevalence of FH worldwide as well as in the UK is 1 in 250-500. Almost 85% of people with FH still remain undiagnosed. FH is predominantly caused by mutations in the three genes LDLR, APOB and PCSK9.

    Aim
    To set up Next Generation Sequencing (NGS) methodology for genetic screening of FH.

    Methods
    A retrospective cohort of 94 patients known and suspected to suffer from FH were selected for targeted sequencing on LDLR, APOB, PCSK9, LDLRAP1 and APOE genes using an Illumina MiSeq system. Data analysis was performed with BaseSpace and Galaxy platforms. Sanger sequencing was performed as a gap filling for NGS.

    Results
    A total of 94 samples were screened by the reference lab of which 58 patients had no reported FH variants. Our NGS approach allowed the identification of FH variants in 62 patients out the 94 samples. Of these, 32 patients had variants identified in LDLR, 27 patients in APOB, 14 patients had variants in APOE and 1 patient had a variant in the PCSK9 gene. Furthermore, 10 patients had variants identified in both LDLR and APOB genes, 4 patients in LDLR and APOE and 3 patients in APOB and APOE.

    Conclusion and impact
    This study has demonstrated the practical utility of NGS as a diagnostic platform for genetic disorders such as FH to be used by the NHS of the future. NGS represents a paradigm shift from the conventional Sanger sequencing in its ever-increasing breadth of coverage, resolution and reliability, coupled with ever-reducing costs. Therefore, incorporation of NGS into routine molecular diagnostics will create a major impact on the way we diagnose and tailor the management of hereditary disorders such as FH.
    Date of AwardNov 2018
    Original languageEnglish
    SupervisorElizabeth Hodges (Supervisor), Sassan Hafizi (Supervisor), Rosalind Ganderton (Supervisor), Darek Gorecki (Supervisor), Sassan Hafizi (Supervisor), Darek Gorecki (Supervisor), Sassan Hafizi (Supervisor) & Darek Gorecki (Supervisor)

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