Genomic analysis of rare disease

Thursday 6 October 2016
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Copy number variation (CNV) contributes as much as 6Mb of the human genome, with an average of 1100 CNVs per individual. As such, the prevalence of CNV suggests that it represents a significant proportion of total genomic variation. CNV occurring within coding or regulatory regions often have an adverse effect on gene expression leading to disease.

Why choose microarrays?

A range of methods are used for genomic analysis, each have strengths and limitations, so often complementary methods are required for comprehensive analysis. Although a powerful technique for genomic analysis, next generation sequencing (NGS) cannot yet reliably detect CNV. Alternative methods such as real-time PCR or multiplex ligation-dependent probe amplification (MLPA) are common. However, they are also low-throughput techniques, and multiple tests are often needed to cover the required number of genes, making them time consuming and expensive to perform. The gold standard for CNV detection is array comparative genomic hybridisation (aCGH)1 which is both a specific and sensitive technique, and also fast and amenable to automation for highthroughput workflows.

Advantage of exon-focused design

While many array platforms carry high numbers of probes, the key to a higher resolution is the number of probes in specific regions of interest. Exon-focused designs such as that of the CytoSure Medical Research Exome array (MREA) enable:

  • High-resolution coverage of the targeted genes
  • Detection of single-exon micro-CNV
  • Identification of more disease-relevant CNVs

OGT inherited disease array solutions

  • Comprehensive, research validated content drawn from multiple databases including ClinVar, OMIM, Orphanet and our collaborators’ own database
  • Highly accurate CNV calling using optimised, pre-validated probe design — for improved coverage and the highest performance

The OGT array provides us with the exon-level resolution needed to detect CNVs over the medical exome that are missed by NGS and traditional microarray designs, providing additional insights into the mutation spectrum of the sample. Dr Emily Farrow, Children's Mercy Hospital, Kansas City, KS, USA

Autism

 

 

 

 

Autism Spectrum Disorders (ASD) are estimated to affect 21.7 million people globally2 and are thought to be highly heritable. However, ASD cannot typically be traced to a Mendelian (single-gene) mutation or to a single chromosome abnormality, and none of the genetic syndromes associated with ASD have been shown to selectively cause ASD.3 The large number of autistic individuals with unaffected family members may result from de novo CNV.4 This hypothesis is supported by the discovery of CNV at 11 loci across 8 chromosomes linked to ASD susceptibility.5 Hence, understanding CNV status in combination with SNV is critical for research into the genetic basis of this disease.

CytoSure Autism Research array:

Number of genes targeted: 227

Examples of diseases covered: Autism, hearing loss, X-linked intellectual disability (XLID).

Epilepsy

 

 

 

 

Epilepsy is a group of neurological diseases characterised by epileptic seizures. The prevalence of Epilepsy is around 1%, meaning that around 65 million people worldwide are living with the disease. Genetics is believed to be involved in the majority of cases, either directly or indirectly. Over 200 single-gene defects have been described6 , but CNV also plays a key role in this disease. One study found 25 of 315 (7.9%) epilepsy patients had CNVs that may contribute to their phenotype.7 A more recent study identified 437 CNV in 323/805 (40%) individuals with epilepsy (1–4 per patient) ranging from 18kb to 142Mb8 , many of which were associated with the disease.

CytoSure Epilepsy Research array:

Number of genes targeted: 212

Examples of diseases covered: Epilepsy, brain malformations, severe combined immune deficiency (SCID).

Neuromuscular disease (NMD)

 

 

 

Neuromuscular disease covers a wide group of diseases affecting voluntary muscles, either directly (affecting muscle function), or indirectly (affecting nerves or neuromuscular junctions). It is estimated that around 160/100,000 population9 are affected by some form of neuromuscular disease. The CytoSure NMD Research array is focused primarily on the muscular dystrophies. Genetic analysis is an important part of research in inherited neuromuscular conditions, and it is important to understand all forms of mutations. In the most common form of muscular dystrophy, Duchenne muscular dystrophy, between 60% and 75% of disease relevant mutations are CNVs.10

CytoSure NMD Research array:

Number of genes targeted: 205

Examples of diseases covered: Duchenne muscular dystrophy (DMD), limb girdle muscular dystrophy (LGMD), congenital muscular dystrophy (CMD), Emery-Dreifuss muscular dystrophy, congenital disorders of glycosylation, maturity onset diabetes of the young.

Cardiomyopathy

 

 

 

 

Cardiomyopathies are diseases of the heart muscle. While the causes of cardiomyopathies are diverse, a proportion are genetic in origin. CNVs have been associated with a number of cardiomyopathies, including long QT syndrome (LQTS)11, 12, and dilated cardiomyopathy (DCM)13 and it is therefore important to include copy number analysis into any research to maximise insights into causal variation. CytoSure

Cardiomyopathy Research array:

Number of genes targeted: 223

Examples of diseases covered: Cardiomyopathies [including long-QT-syndrome (LQTS), dilated cardiomyopathy (DCM), left ventricular noncompaction cardiomyopathy (LVNC)], hereditary haemorrhagic telangiectasia, hereditary neuropathies, connective tissue disorders.

Eye disease

 

 

 

 

CNV as well as SNV play an important role in many kinds of eye disease. CNVs have been described in both relatively common eye disorders such as late age-related macular degeneration14 and intraocular pressure15, as well as rare eye diseases such as Ocular Behcet’s disease16 and Graves ophthalmopathy17. Eye abnormalities are also present in one-third of inherited, systemic diseases. For example, a dislocated lens in the eye is associated with Marfan syndrome, a connective tissue disease associated with heart problems. The CytoSure Eye Disease Research array includes genes important for syndromic and non-syndromic inherited retinal and choroidal dystrophies, as well as ocular developmental disorders.

CytoSure Eye Disease Research array:

Number of genes targeted: 221

Examples of diseases covered: Retinitis pigmentosa, Stargardt disease, macular dystrophy, flecked-retina disorders, congenital stationary night blindness, Bardet-Biedl syndrome, Usher syndrome.

Herditary cancer

 

 

 

 

Many genes have now been identified which affect an individual’s risk of developing cancer during their lifetime, and there are also inherited disorders (such as von Hippel-Lindau syndrome and Lynch syndrome) which have an associated increase in cancer risk (kidney and bowl cancer respectively). CNVs have been strongly associated with a number of cancers including breast cancer, prostate cancer, and nasopharyngeal carcinoma — for example 6p21.3, with single-copy deletion of the MICA and HCP5 genes has been associated with nasopharyngeal carcinoma with an odds ratio of 18.9218. The CytoSure Hereditary Cancer Research array includes genes important in syndromic and non-syndromic inherited cancers.

CytoSure Hereditary Cancer Research array:

Number of genes targeted: 228

Examples of diseases covered: Hereditary cancers, Kabuki syndrome, proportionate short stature, Lynch syndrome.

Metabolic disorders

 

 

 

 

Inherited metabolic diseases comprise a large class of genetic diseases involving disorders of metabolism and while classed as rare disease, as a group are relatively common — as much as one in every 800 live births will have an inherited metabolic disorder.19 The majority are due to defects of single genes that code for enzymes that facilitate conversion of various substances (substrates) into others (products). The metabolic disorders are divided into a number of groups, each still containing many individual disorders, for example there are over 50 lysosomal storage disorders. Due to the large number of metabolic disorders there can be significant heterogeneity between them and understanding the complete genetic picture is made all the more important.

CytoSure Metabolic Disorder Research array:

Number of genes targeted: 203

Examples of diseases covered: Metabolic disorders, lysosomal storage disorders, glycogen storage disorders, mitochondrial disorders (nuclear genes only).

Skeletal dyslapsia

 

 

 

 

Skeletal dysplasia is an umbrella term that includes more than 200 individual inherited conditions that affect bone and cartilage growth. It is typically characterised with short stature and legs, arms, trunk or skull can be of abnormal size and shape. The estimated incidence is 1 in 5000 live births with the most common type being achondroplasia.20 If untreated, skeletal dysplasia can lead to difficulty breathing, including apnea, spinal problems, fluid build-up around the brain, chronic ear infections, and obesity. Hundreds of genes have now been associated with skeletal dysplasia. Using a hand-curated gene list from our development partners at Emory University, the CytoSure Skeletal Dysplasia Research array contains probes targeting 234 medically-relevant genes.

CytoSure Skeletal Dysplasia Research array:

Number of genes targeted: 234

Examples of diseases covered: Skeletal dysplasia, disproportionate short stature, osteogenesis imperfecta, limb malformation.

Ciliopathies

 

 

 

 

Cilia are hair like protuberances from cells with a complex internal structure and can be either motile or immotile. Dysfunctional cilia are known to underlie a number of often chronically disabling conditions. They affect multiple systems, causing blindness, deafness, chronic respiratory infections, kidney disease, heart disease, infertility, obesity and diabetes, and include diseases such as Bardet-Biedl syndrome (BBS) and polycystic kidney disease (PKD). Understanding of the genetic basis of these disorders is improving all the time, but many genes have now been implicated (e.g. PKD2 and PKHD1 in PKD21 and BBS1, BBS7, BBS10, MKKS and ARL6 in BBS22). The CytoSure Ciliopathy Research array covers these genes and many more with a known disease relevance.

CytoSure Ciliopathy Research array:

Number of genes targeted: 207

Examples of diseases covered: Ciliopathies, Joubert syndrome, Stickler syndrome, hyper IgE syndromes, nephronophthisis.

The CytoSure Medical Research Exome array (MREA)

The CytoSure MREA offers comprehensive coverage of over 4600 medically relevant genes at exon-level resolution. This makes it an ideal complement to an exome sequencing approach to provide comprehensive mutation spectrum analysis in rare disease. This array has been developed in collaboration with leading molecular genetics experts at Emory University, working with their hand-curated database of genes to ensure the highest disease relevance of all content. As well as probes for targeted genes, genomic backbone probes are included to ensure identification of novel CNV.

Number of genes targeted: 4645

Custom Array Design

Benefit from our extensive array design expertise to produce an array matching your precise specifications. These arrays are ideal if you want to know the precise coordinates of an aberration by analysing specific areas of the genome at high resolution. Use any of the disease-focused arrays as your starting point and customise to your exacting specifications. Working closely with our experienced design team — one of whom is assigned project leader to ensure continuity of process and communication — the process is made quick, simple and easy.

Custom array design

CytoSure Interpret Software

CytoSure Interpret Software, which is complimentary with all array purchases, offers an impressive combination of features that allow you the choice of standardised data analysis (using the Accelerate Workflow) or customised, user-defined data analysis.

  • Fast, accurate and simple analysis of aCGH data for identification of CNV
  • Comprehensive data annotation with direct links to external databases and online resources
  • Robust relational database allowing sophisticated data querying and filtering
  • Fully integrated, automatic analysis of array image files
  • Includes the new Exon-Focused Segmentation Algorithm (EFSA) designed and tested specifically for exon-focused arrays

Fast and simple access to results using complimentary CytoSure Interpret Software, with comprehensive annotation tracks to aid interpretationFigure 1: Fast and simple access to results using complimentary CytoSure Interpret Software, with comprehensive annotation tracks to aid interpretation

Ordering information

Product Genes Cat. No. Learn more
CytoSure Medical Research Exome array (1x1M) 4645 020100 View product information
CytoSure Autism Research array (4x180k) 227 700121 View product information
CytoSure Epilepsy Research array (4x180k) 212 700112 View product information
CytoSure NMD Research array (4x180k) 205 700117 View product information
CytoSure Cardiomyopathy Research array (4x180k) 223 700110 View product information
CytoSure Eye Disease Research array (4x180k) 221 700113 View product information
CytoSure Hereditary Cancer Research array (4x180k) 228 700115 View product information
CytoSure Metabolic Disorder Research array (4x180k) 203 700116 View product information
CytoSure Skeletal Dysplasia Research array (4x180k) 234 700118 View product information
CytoSure Ciliopathy Research array(4x180k) 207 700111 View product information
CytoSure DMD Research array (8x60k) 50 020023 View product information
CytoSure Custom Molecular array - 700001 View product information
CytoSure Genomic DNA Labelling Kit - 020022 View product information
CytoSure HT Genomic DNA Labelling Kit - 500040 View product information
CytoSure Sample Tracking Spike-ins A – H - 500050 – 500057 View product information
CytoSure Interpret Software - N/A View product information

 

References

  1. Curtis, C. et al (2009) The pitfalls of platform comparison: DNA copy number array technologies assessed. BMC Genomics 10, 588-610
  2. Global Burden of Disease Study 2013 Collaborators (2015). Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386 (9995), 743–800 
  3. Abrahams, B.S. and Geschwind, D.H. (2008) Advances in autism genetics: on the threshold of a new neurobiology. Nature Reviews Genetics 9 (5), 341–55. 
  4. Cook, E.H. and Scherer, S.W. (2008) Copy-number variations associated with neuropsychiatric conditions. Nature 455 (7215), 919–23. 
  5. Menasha, I. et al (2013) Prioritization of Copy Number Variation Loci Associated with Autism from AutDB–An Integrative Multi-Study Genetic Database. PLOS one 8 (6), e66707 
  6. Kumar, D. ed. (2008) Genomics and clinical medicine. Oxford: Oxford University Press. p. 279.
  7. Mefford, H.C. et al (2011) Rare copy number variants are an important cause of epileptic encephalopathies. Annals of Neurology 70, 974–985 
  8. Olson, H. et al (2014) Copy number variation plays an important role in clinical epilepsy. Annals of Neurology 75(6), 943–958 
  9. Deenen, J.C.W. et al (2015) The Epidemiology of Neuromuscular Disorders: A Comprehensive Overview of the Literature. Journal of Neuromuscular Disease 2(1) 73-85 
  10. Prior, T.W. and Bridgeman, S.J. (2005) Experience and Strategy for the Molecular Testing of Duchenne Muscular Dystrophy. J Mol Diagn. 7(3) 317-26 
  11. Eddy, C.A. et al (2008) Identification of large gene deletions and duplications in KCNQ1 and KCNH2 in patients with long QT syndrome. Heart Rhythm 5, 1275–1281 
  12. Tester, D.J. et al (2010) Prevalence and spectrum of large deletions or duplications in the major long QT syndrome-susceptibility genes and implications for long QT syndrome genetic testing. Am J Cardiol 106, 1124–1128 
  13. Norton, N. et al (2011) Genome-wide studies of copy number variation and exome sequencing identify rare variants in bag3 as a cause of dilated cardiomyopathy. Am J Hum Genet. 88, 273-82 
  14. Cantsilieris, S. et al (2012) Comprehensive Analysis of Copy Number Variation of Genes at Chromosome 1 and 10 Loci Associated with Late Age Related Macular Degeneration. PLoS ONE 7(4) e35255 
  15. Nag, A. et al (2013) Copy number variation at chromosome 5q21.2 is associated with intraocular pressure. Invest Ophthalmol Vis Sci., 54 3607–3612 
  16. Fang, J. et al (2015) Association between copy number variations of TLR7 and ocular Behcet’s disease in a Chinese Han population. Invest Ophthalmol Vis Sci., 56 1517–1523. 
  17. Liao, W. et al (2014) Association of TLR7 and TSHR copy number variation with Graves’ disease and Graves’ ophthalmopathy in Chinese population in Taiwan. BMC Ophthalmology, 14 15 
  18. Tse, K.P. et al (2011) A Gender-Specific Association of CNV at 6p21.3 with NPC Susceptibility. Human Molecular Genetics, 20, 2889-2896. 
  19. Sanderson, S. et al (2006) The incidence of inherited metabolic disorders in the West Midlands, UK Arch Dis Child 91, 896–899. 
  20. Orioli, I.M. et al (1986) The birth prevalence rates for the skeletal dysplasias. J Med Genet 1986;23:328 –332. 
  21. Gunay-Aygun, M. (2009) Liver and kidney disease in ciliopathies. Am J Med Genet C Semin Med Genet. 151C (4): 296–306. 
  22. Ross, A. et al (2008) The clinical, molecular, and functional genetics of Bardet-Biedl syndrome, in Genetics of Obesity Syndromes. Oxford University Press. p. 177

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