Feasibility of Screening for Chromosome 15 Imprinting Disorders in 16 579 Newborns by Using a Novel Genomic Workflow

Key Points Question Is newborn screening feasible for chromosome 15 imprinting disorders, including Prader-Willi, Angelman, and Dup15q syndromes, using SNRPN methylation analysis? Findings This diagnostic study involved validation of a novel methylation test on 1356 samples, showing high sensitivity and specificity and positive and negative predictive values to differentiate newborn blood spots and blood, saliva, and buccal DNA of 109 Prader-Willi, 48 Angelman, and 9 Dup15q patient samples from neurotypical control samples. Newborn blood spots from 16 579 infants from the general population were then tested, identifying 2 with Prader-Willi syndrome, 2 with Angelman syndrome, and 1 with Dup15q syndrome. Meaning The findings of this study suggest that it is feasible to screen for all chromosome 15 imprinting disorders using SNRPN methylation analysis.

and (iii) family support groups. The infant test cohort utilized for prevalence studies included 15,749 NBS consented in 2011, and 830 consented in 2016 for de-identified research at part of greatly from use of fresher samples in this test cohort, ethics approval did not permit for this to occur. The study was required to screen only the NBS consented for de-identified research from 2011 population sample because by 2016 (when the samples were screened in this study) most children from this cohort should have received their diagnosis by standard of care testing. This in turn minimized potential ethical issues associated with not returning the results for the probands identified from this study.
Briefly, for the test cohort all NBS were punched into 3 replicate 96 well plates (eFig 1). The first two plates had a single 3mm NBS punch per infant per well, while the third plate had three 3mm punches per well. The first plate was used for 1 st -tier testing utilizing MS-QMA to analyze methylation of the SRNPN promoter. The second and third plates were used for precise quantitation of SNRPN promoter DNA methylation using CINQ ddPCR and a SNRPN real-time PCR CNV analysis to detect changes in copy number at the SNRPN locus.
Samples confirmed by 2 nd -tier testing to have an abnormal CNV result were referred to 3 rd -tier testing involving LC-WGS from the third plate (eFig 1).

eAppendix 2. MS-QMA testing.
Two separate bisulfite conversions were performed per patient sample, as previously described 18 . Ninety-six samples were bisulfite converted at a time (3 controls and 93 unknown samples per plate) and were serially diluted once post-conversion. Each set of four 96 well plates was then transferred into a 384 well format for real-time PCR analysis utilizing The unknown samples that did not have DNA concentration post-bisulfite conversion within this dynamic linear range, were flagged by the Q-MAX software as not meeting this quality control parameter prior to the HRM analysis (that would follow in close tube format).
The products from methylated and unmethylated SNRPN promoter sequences were then separated into single strands in the temperature range of 76.5°C and 84.5°C. The HRM software module for ViiA™ 7 System was then used to plot the rate of PCR product separation to single strands at different temperatures with the difference in fluorescence converted to aligned fluorescence units (AFU) at 80°C. The AFU conversion to the methylation percentage, and all of the above quality control steps, were analyzed simultaneously for 384 reactions at a time using Q-MAX software (Curve Tomorrow, Melbourne, Australia), developed to automate the process.
This software utilized a custom-designed computer algorithm to simultaneously perform multiple quality control checks to determine DNA concentrations and quality postbisulfite conversion using raw real-time PCR data, as well as, uniformity of HRM profile data outputs between 4 technical replicates per sample (2 bisulfite reactions and 2 dilutions [1 per conversion]). The HRM data for the sample dilutions outside the QC ranges were automatically discarded and were not included inthe quantitative methylation analysis by the Q-MAX software, as previously described 18 .   Inter-run variability was assessed for quantitative analysis of SNRPN promoter using MS-QMA on six DNA samples with different levels of SNRPN methylation achieved through spiking an AS sample showing 0% SNRPN methylation with a PWS sample showing 100% SNRPN methylation (eFig 3). The MS-QMA output was highly reproducible over the 8 runs at 0%, 87%, 95% and 100% methylation, with 2 standard deviations of 1%, 3%, 4% and 2%, respectively. As methylation levels approached 50%, the technical variability between runs increased, with 2 standard deviations of 8%.
The method was then applied to 1,356 samples. There was one false positive result (yellow dot Fig 1) and one PWS NBS and 2 Dup15 NBS showing a false negative results. All AS NBS/DBS cases other than those caused by a UBE3A sequence mutation, had methylation ratio approaching 0 and were correctly identified by MS-QMA to be in the AS methylation range. As expected, DBS from AS due to a UBE3A sequence mutation showed SNRPN methylation approaching 50% and could not be differentiated from general population controls.      eFigure 6. Examples of 2-D plots from CINQ ddPCR for NBS confirmed to have abnormal SNRPN methylation co-run with DBS from positive and negative controls. Note: each blue dot indicated data from a single ddPCR droplet; each column contains data for a single sample; purple line indicates amplitude cut-off above which all droplets were considered to have positive signal above background; red horizontal line is the amplitude cut-off above which all droplet signals were considered to be from maternal alleles with methylated SNRPN; droplet with amplitude between purple and red line cut-offs were considered to be from paternal alleles with unmethylated SNRPN; red M = methylated allele signal; green UM = unmethylated allele signal; PWS(c) = PWS positive control DBS; AS(c) = AS positive control DBS; GP(c) = general population infant DBS negative control; NTC = no template control.