HGSA 2024

Familial Adult Myoclonic Epilepsy (FAME) is characterised by cortical tremor, myoclonus and myoclonic and / or generalised tonic-clonic seizures with onset in the 2nd to 3rd decade. FAME is caused by non-coding, intronic expansions of a reference TTTTA DNA motif adjacent to an inserted and repeated TTTCA motif in one of seven different genes with unrelated molecular functions. Guidelines for clinical molecular tests for FAME are currently not available and the pathogenic limits on repeat length or the effects of different motifs within the repeat are not known. We previously showed that the age of disease onset significantly decreased over three successive generations in a large Australian / NZ family with FAME2. We hypothesised that this anticipation correlated with the length of the TTTTA and TTTCA repeat expansion. We measured the length of FAME TTTTA and TTTCA repeats in DNA extracted from blood of 94 affected individuals from 10 FAME2 families using long-range PCR and Oxford nanopore DNA sequencing. The average length of the entire repeat increased in successive generations in multiple FAME2 families and correlated with younger age of onset of myoclonus (r=-0.329, p=0.05). There were no significant differences in the magnitude of changes in repeat lengths between maternal or paternal inheritance. Changes in numbers of both TTTTA and TTTCA repeats over successive passages of patient-derived lymphoblastoid and primary skin fibroblast cell lines were dynamic;potentially modelling somatic instability. High levels of motif and repeat length variation at FAME loci were observed in population controls from the gnomAD database and individuals we sequenced. Our results collectively suggest that TTTTA and TTTCA repeat expansions are dynamic during both meiosis and mitosis, with longer overall length correlating with earlier disease onset and motif structures that may lead to false negative results using some diagnostic methods.

There are ~200 children in high dependency neonatal acute care in New Zealand at any one time, requiring a scalable distributed solution for acute care genomics. We have established an expandable acute care clinical pipeline based around the PromethION2 solo system with connection to Fabric GEM™. In the establishment phase, we have performed benchmarking using GA4GH benchmarking tools and Genome in a Bottle HG002 - HG007. Evaluating ~3.3x106 truth SNVs and ~500x103 INDELS at read depths of between 24-42X coverage identified SNV recalls = 0.992 ± 0.001, precision = 0.997 ± 0.0006, and F1 = 0.995 ± 0.0008 over a minimum of two runs completed by different technicians and analysts. INDEL identification approached recalls = 0.838 ± 0.043, precision = 0.922 ± 0.019, and F1 = 0.874 ± 0.032 over the same runs. Subsequent analyses indicated that the observed variation in recall, precision and F1 was largely limited to correct copies of falsely duplicated regions and areas of collapsed errors with clusters of CHM13 hets in GRCh38. Rarefaction analyses up to 80X coverage identified that SNV identification plateaus at ~20X coverage, while INDEL identification plateaus at ~40X coverage. Analyses of samples from Coriell CNVPANEL01 demonstrated that large scale genomic variations can be reliably detected after ~2M reads, equivalent to ~2hr sequencing time. Application of the pipeline in acute care genomic diagnosis is ongoing. We present the preliminary results from the pipeline validation phase, performed in parallel with established International accredited facilities available to New Zealand’s clinicians.

A paradigm shift in genomics is upon us. As DNA/RNA sequencing improves in breadth and accuracy and becomes more cost efficient, global health systems and diagnostic industries are slowly realizing that the benefit of genomic and other omic screening to patients is finally aligning with the economics of making it available more broadly. The significant benefits of third-generation sequencing, or, long-read sequencing, include richness of data, speed, accuracy, affordability and an accessible design, all of which have a profound opportunity to make an impact. But this ambition is not without its challenges, and scaling this technology across health systems will require a population health approach. Broadly defined, population health refers to the health status and health outcomes of a group of people, rather than just the individual. Population health includes consideration of health determinants, such as health inequalities and distribution of health across subpopulations, and the interventions and policies that link health outcomes with health determinants. A goal of population health is to improve health by reducing risk of disease through early detection, in part through broad deployment of precision medicine tools, throughout the life journey. As the technology improves and the economics of sequencing shift, so do the opportunities to engage health systems on a mass scale.