Development of a Targeted Multi-Disorder High-Throughput Sequencing Assay for the Effective Identification of Disease-Causing Variants

<div><p>Background</p><p>While next generation sequencing (NGS) is a useful tool for the identification of genetic variants to aid diagnosis and support therapy decision, high sequencing costs have limited its application within routine clinical care, especially in economically depressed areas. To investigate the utility of a multi-disease NGS based genetic test, we designed a custom sequencing assay targeting over thirty disease-associated areas including cardiac disorders, intellectual disabilities, hearing loss, collagenopathies, muscular dystrophy, Ashkenazi Jewish genetic disorders, and complex Mendelian disorders. We focused on these specific areas based on the interest of our collaborative clinical team, suggesting these diseases being the ones in need for the development of a sequencing-screening assay.</p><p>Results</p><p>We targeted all coding, untranslated regions (UTR) and flanking intronic regions of 650 known disease-associated genes using the Roche-NimbleGen EZ SeqCapV3 capture system and sequenced on the Illumina HiSeq 2500 Rapid Run platform. Eight controls with known variants and one HapMap sample were first sequenced to assess the performance of the panel. Subsequently, as a proof of principle and to explore the possible utility of our test, we analyzed test disease subjects (n = 16). Eight had known Mendelian disorders and eight had complex pediatric diseases. In addition to assess whether copy number variation may be of utility as a companion assay relative to these specific disease areas, we used the Affymetrix Genome-Wide SNP Array 6.0 to analyze the same samples.</p><p>Conclusion</p><p>We identified potentially disease-associated variants: 22 missense, 4 nonsense, 1 frameshift, and 1 splice variants (16 previously identified, 12 novel among dbSNP and 15 novel among NHLBI Exome Variant Server). We found multi-disease targeted high-throughput sequencing to be a cost efficient approach in detecting disease-associated variants to aid diagnosis.</p></div

Summary of sequencing coverage and detected variants for test cohort.

<p>* indicates samples that were multiplexed together.</p><p>TG471.002 was added to another lane for logistic reasons.</p><p>Summary of sequencing coverage and detected variants for test cohort.</p

Cost comparison of target sequencing panel Einstein_v1 versus Whole Exome Sequencing.

<p>* The number of SNVs/InDels identified was based on samples used in the current analysis (n = 2 for WES and matching target sequencing).</p><p>** Based on estimated $1,400/lane 150 bp pair end sequencing on Illumina 2500.</p><p>Cost comparison of target sequencing panel Einstein_v1 versus Whole Exome Sequencing.</p

Custom panel design.

<p>The pie chart illustrates the percent of genes included in the custom design categorized based on specific diseases/abnormalities. Of note the Ashkenazi Jews variant disorders have been kept separate because they represent an ethnic division commonly associated with specific disease and genetic variants.</p

Demographic, clinical features, and sequencing results of the sixteen patients in test cohort.

<p>Legend: Ethnicitiy: AA = African American, Cau = Caucasian, His = Hispanic, Isr = Israeli, Ben = Bengali, Mex = Mexican, N/A = Not Available; Clinical Information: DD = Developmental Delay, DF = Dyspmorphic Features, MCA = Multiple Congenital Anomalies, FSGS = Focal segmental glomerulosclerosis, ID = Intellectual Disability, VSD = Ventricular Septal Defect, SD = Speech Delay, PDD = Pervasive Developmental Delay, DCM = Dilated Cardiomyopathy, LQTS = Long QT Syndrome, CPVT = Catecholaminergic Polymorphic Ventricular Tachycardia, SPOH = Severe Postural Orthostatic Hypertension, HCM = Hypertrophic Cardiomyopathy.</p><p>Demographic, clinical features, and sequencing results of the sixteen patients in test cohort.</p

Project pipeline.

<p>Sample quality is conducted in the laboratory (blue box), subsequent library prep and sequencing is conducted in the Epigenomics Shared Facility (pink box). The sequence reads automatically progress into the WASP pipeline for quality control parameters, alignment to reference sequence through BWA and duplicate removal through Picard is performed (yellow boxes). Local Realignment, base quality recalibration, variant discovery and annotation take place via GATK or VarScan2 (somatic) (green boxes). Clinically relevant variants are prioritized through Alamut and visualized through IGV (orange boxes). Validation is then performed by Sanger sequencing and results are visualized through Sequencher 4.0.1 (purple box).</p

Mutational pedigree of TG471.001 and TG472.002, sisters with DCM.

<p>Affected sisters are indicated in black. Associated variants are provided under each family member.</p

Mosaic Epigenetic Dysregulation of Ectodermal Cells in Autism Spectrum Disorder

<div><p>DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder.</p></div

Genes associated with the DMRs identified by bump-hunting.

<p>CNV: copy number variant.</p

Biological and technical confounders contribute to methylation value variation.

<p>The heat map displays the –log₁₀ p-values of the linear regressions of the top ten principal components onto each known covariate. The color key shows corresponding numeric values, with red indicating increased significance. The majority of variation is accounted for by experimental influences, with age and ancestry also contributing significantly to variation.</p