Shifting the Patient Paradigm
The Greenwood Genetic Center (GGC) has embarked on a novel program to leverage traditional and emerging genomic technologies, in the search for answers for undiagnosed patients.
In the 43 years since the Greenwood Genetic Center (GGC) was founded, we have witnessed tremendous advances in genetic testing and genomic technology. Despite the amazing advances in our knowledge and technology, far too many of our patients still remain without a definitive diagnosis, especially for rare diseases. We are unwilling to accept that so many of our patients remain on a diagnostic odyssey — going from specialist to specialist having test after test with no clear answers, no specific treatment plan, and, often times, no hope.
To change this paradigm and better serve our patients, GGC has embarked on a novel program called Technology and Genomics Enhancing Medicine (TGEM), an initiative to systematically leverage traditional and emerging genomic technologies in the search for answers for undiagnosed patients.
The goal of TGEM is to increase GGC’s diagnostic yield by an additional 20% in the next three years.
TGEM is a comprehensive testing strategy applied to a wide variety of patients from newborns to adults – patients for whom current testing methodologies have failed to provide a definitive genetic diagnosis. TGEM combines six genomic testing strategies with machine learning to synergise these emerging genomic technologies to increase diagnostic yield with the ultimate goal of providing answers and treatments for patients.
1. Whole Genome Sequencing (WGS)
Sequencing of nearly every nucleotide in the human genome is intended to provide the greatest level of genetic resolution currently possible. And even though generating whole genome data has been possible for some time now, it is not routine, easy to access or even an affordable option for many. The high cost involved includes the expense of equipment and reagents, the involved bioinformatics processes, the cost of data storage and management, as well as the variant interpretation that provides relevance in the clinical context of any given individual.
Large genome centres appear, at least for the time being, to have the upper-hand in terms of generating and managing genomic data; however, smaller and perhaps more clinically-focused diagnostic labs shouldn’t attempt to work in this space. The challenge for labs such as GGC’s Molecular Diagnostic Laboratory is to select the best package of solutions to create an environment capable of managing and interpreting whole genome data. Most labs offering WGS continue to review the data through an “exomic” lens, given the difficulty in meaningfully interpreting novel variants when they don’t have an obvious or predicted effect on the coding sequence of any given gene. But, when there is not a clear-cut answer to be had using standard testing approaches, the hope is that WGS will provide the greatest number of answers for many patients, now and well into the future.
2. RNA Sequencing
The profiling of complex gene expression patterns has the potential to become immensely helpful as a diagnostic tool for many types of conditions. Examining the transcriptome with RNASeq goes beyond the relatively static nature of sequencing genomic DNA. It provides the ability to look at expression patterns in large-scale beyond targeted analysis of single genes. Changes in expression patterns may be immediately apparent for specific diseases, but for most conditions, perturbations may be quite subtle and more difficult to discern. This is likely true for most rare diseases given the number of permutations possible as specific biological pathways are impacted due to single gene mutations.
There are great expectations for the future of RNASeq although it’s clear that many challenges remain. Most of the primary hurdles will be overcome with better and more sophisticated bioinformatic algorithms. The current limitations in this area explain why most diagnostic laboratories have not yet ventured into this space. Time and even more energy needs to be invested for the full potential of RNASeq to be realized. One of the best strategies to learn more will be to have larger cohorts with the same proven condition grouped and analyzed. The diagnostic future for RNASeq is bright as its full capabilities are harnessed.
3. XON Array
Chromosomal microarray has been a part of clinical diagnostics for the past decade and has been recommended by the American College of Medical Genetics and Genomics as a first tier test for individuals with birth defects, intellectual disability, dysmorphic features, autism and developmental delay. A number of high-resolution SNP microarray platforms are available to identify microdeletions/microduplications and uniparental disomies. However, the additional ability to pick up single exon level deletions/duplications of the genes that comprise the clinical/medical exome can be of immense benefit to the accurate diagnosis of genomic disorders.
The GGC Microarray Laboratory has been part of the design, development, and early access studies of the Applied Biosystems™ CytoScan™ XON Suite from Thermo Fisher Scientific, an exon level, high-resolution array platform with 6.85 million probes covering approximately 26,000 genes. A cross-platform comparison allowed the laboratory to determine the clinical utility and clinical validity of this test. Our pilot study identified a unique case with a rare biallelic deletion involving SOX10 (Waardenburg Syndrome Type IV). This platform also has the ability to pick up rare, single or multi-exon deletions/duplications in genes associated with autosomal recessive disorders in cases where only a single nucleotide change had been identified by sequencing methodologies. GGC will be using this platform as a complement to whole exome sequencing platform and as a reflex test in cases where sequencing results are negative. Our goal in employing this technology is to identify unique and rare microdeletions/microduplications at the single exon level in genes associated with genetic disorders in an effort to quickly and accurately diagnose patients for effective clinical management.
4. DNA Structural Variant Analysis
Clinical cytogenomics is primarily the study of chromosomes and their structural variations. For the past five decades, structural variations (SVs) have been known to play a significant role in both constitutional disorders and neoplasias. Globally, clinical cytogenomics is routinely used as a diagnostic assay/test to identify and diagnose genomic disorders, such as those causing pregnancy losses, congenital anomalies, and intellectual disability. Also, many malignancies, including leukemia’s, lymphomas and solid tumors, have been characterised with hallmark SVs that may be both diagnostic and prognostic, and can help pave the way for an appropriate therapeutic regimen. Historically, karyotyping and fluorescence in situ hybridisation (FISH) are the gold standard cytogenetic techniques used throughout the world. However, karyotyping has a limit of resolution of 5-10 Mb and cannot pick up cryptic SVs. FISH is only useful when the genomic loci of interest is known. Newer technologies such as microarray and NGS have picked up pace in clinical diagnostics. However, since the majority of the human genome is made up of repetitive sequences, short-read sequencing data from NGS maps with poor accuracy to these repeats. Short reads cannot provide unambiguous information across repeat elements longer than individual reads or read pairs. When hybridisation-based methods like chromosomal microarrays are used, the length of the hybridisation probes is also too short to span these repeats.
Bionano Genomics’ whole genome mapping (WGM) technology is an optical mapping approach, combining the advantages of several different molecular technologies while removing many of the limitations. Megabase sized molecules of genomic DNA are labelled, linearised, uniformly stretched in high-density NanoChannel arrays, and imaged on the Saphyr instrument. De novo, chromosome-arm length genome maps are built from the imaged molecules, and all major types of structural variants are called automatically. Compared to conventional cytogenetics, Bionano mapping has much greater throughput and removes manual interpretation. It also offers much higher resolution, detecting unbalanced events starting at 500 bp and balanced events as small as 30 kbp versus the multi-megabases needed for cytogenetic approaches. Compared to NGS, Bionano mapping’s extremely long molecules can span repetitive sequences and detect balanced events no matter where in the genome they occur.
At GGC, we are utilising Bionano’s genome mapping to identify previously unknown causes for several birth defects, including neural tube defects, VACTERL anomalies, and split-hand/foot malformations. Our goal is to increase in diagnostic yield and assess whether whole genome mapping may be a technology that revolutionises “Next Generation Cytogenomics”.
5. Methylation Array
DNA methylation arrays can provide information beyond the sequencing data of NGS and copy number variations of microarray by assessing epigenetic modifications which can alter gene expression. Methylation changes are known to modify the function of regulatory elements and cause dysregulation of normal gene functions, causing a disease phenotype. Clinical testing already takes advantage of changes in methylation for imprinting disorders such as Prader-Willi, Angelman, and Beckwith Wiedemann syndromes, uniparental disomy syndromes such as Russell Silver syndrome and UPD14, and even in cancers, including Lynch syndrome, retinoblastoma and glioblastoma. Bekim Sadicovic at London Health Sciences Center at Western University in Canada and Charles Schwartz at GGC has used an Illumina methylation array to show that this technology is a potential method for the diagnosis of other syndromes as well. They have recently published papers(1,2,3) showing altered and specific methylation patterns in a number of syndromes including Kabuki, ATRX, Sotos, CHARGE, Floating Harbor and Claes-Jensen syndromes. Using these “epi-signatures” they have been able to reclassify variants of uncertain significance (VUS) in the Kabuki syndrome gene, KMT2D, to pathogenic or benign based on the epi-signature. For X-linked Claes-Jensen intellectual disability syndrome, they have been able to distinguish separate epi-signatures for both affected males and carrier females. Thus, the methylation array should prove helpful for individuals with intellectual disability, as the differential diagnosis can be quite complex with overlapping phenotypes. As the number of defined epi-signatures increases, this array could be useful as a screening tool for patients with developmental and intellectual disability disorders.
GGC recently began offering an untargeted metabolomic profiling test called MetaSign that can be used to screen for a broad range of metabolomic abnormalities. This semi-quantitative test is focused on detecting perturbations in individual small molecules, thereby elucidating the effects on the associated biochemical pathways. MetaSign typically identifies ~800 small molecules in a single plasma sample. Metabolomic profiling can be useful for patients with broad and/or vague phenotypes, such as hypotonia, non-syndromic intellectual disability, developmental delay, staring spells/seizures, and abnormal movements. It can also be useful in evaluating variants of unknown significance from WES/NGS panels. Metabolomic profiling should also be considered in cases of rare disorders that do not have a clinically available targeted test, as well as those that require invasive targeted testing such as a liver or muscle biopsy. For patients with rare disorders and undifferentiated phenotypes, using a targeted testing approach makes determining a diagnosis nearly impossible and consumes significant resources and time. Further, an untargeted approach provides the flexibility to have a broad differential spectrum. Observing perturbations of several metabolites within a pathway provides more confidence in the diagnosis, better identification of a dysfunctional enzyme, and improved understanding of the biochemical mechanism of rare disorders.
In GGC’s experience to date, metabolomic profiling has helped diagnose several rare and ultra-rare disorders including a carrier female expressing ornithine transcarbamylase deficiency, a patient with adenylosuccinate lyase deficiency, and a patient with homozygous variants of unknown significance in ALDH18A1. The information gleaned from metabolomic profiling is also being used to help guide treatment plans. Even in situations where no effective treatment is readily available, our patients and families express great solace when, after months or years of searching, they finally receive the correct diagnosis. Metabolomic profiling is playing an important role in bringing an end to the diagnostic odysseys for many patients and their families by providing answers and most importantly, hope.
Each of these six technologies are powerful individually and offer significant promise to provide diagnoses for patients. Each of these technologies creates their own challenges with bioinformatics, analysis and interpretation. However, our hypothesis is that the greatest advances and highest yield from these technologies will be achieved by the systematic application of these technologies on undiagnosed patients in an integrated manner. Equally critical to the success of this initiative will be the integrated analysis of data from each of these technologies utilizing machine learning.
TGEM is an ambitious and broad initiative designed to significantly increase the diagnostic yield for patients who remain on their diagnostic odyssey despite utilization of current genomic technologies and approaches. TGEM is a result of GGC’s commitment to compassion inspiring progress as we strive to provide answers, treatments and hope for our patients.
- Aref-Eshghi E, Schenkel LC, Lin H, Skinner C, Ainsworth P, Paré G, Rodenhiser D, Schwartz C, Sadikovic B. The defining DNA methylation signature of Kabuki syndrome enables functional assessment of genetic variants of unknown clinical significance. Epigenetics. 2017 Sep 21 PMID: 28933623.
- Schenkel LC, Aref-Eshghi E, Skinner C, Ainsworth P, Lin H, Paré G, Rodenhiser DI, Schwartz C and B Sadikovic. Peripheral blood epi-signature of Claes-Jensen syndrome enables sensitive and specific identification of patients and healthy carriers with pathogenic mutations in KDM5C. Clinical Epigenetics (2018) 10:21 https://doi.org/10.1186/s13148-018-0453-8
- Aref-Eshghi E, Rodenhiser DI, Schenkel LC, Lin H, Skinner C, Ainsworth P, Paré G, Hood RL, Bulman DE, Kernohan KD; Care4Rare Canada Consortium, Boycott KM, Campeau PM, Schwartz C, Sadikovic B. Genomic DNA methylation signatures enable concurrent diagnosis and clinical genetic variant classification in neurodevelopmental syndromes. Am J Hum Genet. 2018 Jan 4;102(1):156-174. doi: 10.1016/j.ajhg.2017.12.008.