To Örebro University

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) and other disorders with similar features are common genetic disorders that remain underdiagnosed and undertreated, due in part to the cost of screening. The aim of this study was to design and implement a whole gene targeted NGS panel for the molecular diagnosis of FH and statin intolerance with an emphasis on high quality variant calling, including copy number analysis.

METHODS: A whole gene panel for hybridisation-based short read NGS was designed for the dominant FH-genes low density lipoprotein receptor (LDLR), apolipoprotein B (APOB), proproteinconvertas subtilisin/kexin type 9 (PCSK9), apolipoprotein E (APOE) and the recessive FH-genes low density lipoprotein receptor adaptor protein 1 (LDLRAP1), ATP binding cassette subfamily member 5/8 (ABCG5/8) and lipase A, lysosomal acid type (LIPA), as well as solute carrier organic anion transporter family member 1B1 (SLCO1B1), not an FH gene but linked to statin intolerance. Polygenetic risk score markers were also included. The panel was used for screening of a Swedish FH-study population (n = 133).

RESULTS: The panel sequencing resulted in high coverage and confident variant calling of included genes. Known causal variants were found in common dominant FH-genes in 43 % of the cohort. Copy number variants were found in LDLR in 10 individuals and a whole gene deletion of SLCO1B1 in one individual. In addition, coding variants in recessive genes and rare non-coding intronic and untranslated region variants were found in a large proportion of the study individuals highlighting the need for extended gene panels.

CONCLUSIONS: This new tool can be used for a comprehensive high-quality molecular genetic analysis according to guidelines for the diagnosis and treatment of FH.

Sudden unexpected death (SUD) is an unexpected event that in many cases are caused by diseases with an underlying genetic background. Forensic molecular autopsy is an approach that has gained wide-spread attention, in part explained by the rapid progress of DNA sequencing techniques. The approach leverages genetic data in combination with medical autopsy findings in post-mortem samples to explore a potential underlying genetic cause of death. Traditional forensic approaches to molecular autopsy focus on a small panel of genes, say <200 genes, with strong association to heart conditions whereas clinical genetics tend to capture entire exomes while subsequently selecting targeted panels bioinformatically. The drop in price and the increased throughput has promoted wider exome sequencing as a viable method to discover genetic variants. We explore a targeted gene panel consisting of 2422 genes, selected based on their broad association to sudden unexplained death. A hybridization capture approach from Twist Bioscience based on double stranded DNA probes was used to target exons of the included genes. We selected and sequenced a total of 98 post-mortem samples from historical forensic autopsy cases where the cause of death could not be unambiguously determined based on medical findings and that had a previous negative molecular autopsy. In the current study, we focus on the performance of the hybridization capture technology on a 2422 gene panel and explore metrics related to sequencing success using a mid-end NextSeq 550 as well as a MiSeq FGx platform. With the latter we demonstrate that our sequence data benefits from 2×300 bp sequencing increasing coverage, in particular, for difficult regions where shadow coverage, i.e. regions outside the probes, are utilized. The results further illustrate a highly uniform capture across the panel of genes (mean fold80=1.5), in turn minimizing excessive sequencing costs to reach sufficient coverage, i.e. 20X. We outline a stepwise procedure to select genes associated with SUD through virtual bioinformatical panels extracting tier of genes with increasing strength of association to SUD. We propose some prioritization strategies to filter variants with highest potential and show that the number of high priority genetic variant requiring manual inspections is few (0-3 for all tiers of genes) when all filters are applied.

OBJECTIVE: Clinical validation of sperm selection device ZyMōt™ for standard IVF.

METHODS: The pre-clinical validation of ZyMōt™ included several steps. First, split semen preparation compared density gradient centrifugation (DGC) to ZyMōt™ with primary outcome fraction and absolute number of progressive motile sperm. Second, sibling oocytes were fertilized with sperms prepared with DGC and sperms selected by ZyMōt™, primary endpoint fertilization rate, utility rate, embryo development pace quality. After this, DGC was replaced by ZyMōt™, first without centrifugation steps, and then with a five-minute centrifugation step and subsequent media change prior to gamete co-incubation. Endpoint was assessment of key performance indicators against previous results using DGC for standard IVF.

RESULTS: ZyMōt™ resulted in purer sperm selection compared to DGC (fraction progressive motile sperm 97.2±3.1% vs. 83.0±14.1%, p<0.01). Fertilization of sibling oocytes resulted in similar fertilization rates and utility rates, and no differences in embryo development pace or quality. However, after changing sperm selection protocol from DGC to ZyMōt™ for standard IVF for all fresh semen samples with motile sperm, the fertilization rates and utility rates were significantly reduced, and cases of total failure of fertilization increased substantially. Adding five-minute centrifugation and media change after centrifugation to the sperm selection protocol restored fertilization rate, including total failure of fertilization rate, to normal.

CONCLUSIONS: To conclude, the ZyMōt™ sperm selection device is suitable for standard IVF only after inclusion of five minutes centrifugation and subsequent media change prior to gamete co-incubation.

Background/Objectives: Familial hypercholesterolemia (FH) is a common genetic disorder which is primarily caused by pathogenic variants in the LDLR, APOB, and PCSK9 genes. Approximately 10% of pathogenic variants in LDLR may be CNVs. Here, we combine NGS, MLPA, and Optical Genome Mapping (OGM) to investigate CNVs in LDLR.

Methods: A NGS panel was designed for whole gene sequencing (8 genes) of 100 FH patients using Twist technology and Illumina platform. CNVs were detected using CNVexpo, and an in-house pipeline for base-resolved normalized coverage. Identified CNVs were validated using MLPA and OGM. Bionano Services Lab performed the OGM procedure. Purified gDNA was labeled using Direct Label and Stain DNA Labeling Kit. Saphyr chip was run aiming for 100X coverage. De novo assembly and Variant Annotation pipelines were executed on Bionano Solve v3.7. Bionano Access v1.7 was used for CNV reporting and visualization.

Results: In five out of 100 samples NGS and MLPA data showed heterozygous deletions in LDLR. Three deletions, affecting different exons, was analyzed and confirmed using OGM. In two samples, OGM better defined the breakpoints as well as the size of the event, which expanded far beyond the gene of interest. In one sample, an additional CNV of SLCO1B1, a pharmaco-gene, important for transport of statins used for FH treatment was identified.

Conclusion: CNVs in FH genes in FH patients could be detected using targeted NGS, which was further confirmed by MLPA and characterized using OGM.

PURPOSE: Map the nuclear error phenotypes in the two-cell embryo after assisted reproduction using time lapse images and the effect on good quality blastocyst formation.

METHODS: Retrospective cohort study using time lapse images, categorizing 2331 two-cell embryos from 392 patient couples and 504 ART cycles categorizing each embryo as mononucleated, multinucleated, micronucleated, binucleated, split nucleation or mixed error. Correlating nuclear error phenotype with good quality blastocyst formation rate (BFR) using contingency tables and unadjusted odds ratio.

RESULTS: An overall nuclear error rate of 47.1% was observed in two-cell embryos. The most frequent error was multi-nucleation (14.2%) followed by mixed error (11%), micro-nucleation (8.6%), bi-nucleation (7.4%) and split nucleation (5.8%). Blastocyst formation rate (BFR) was reduced in embryos with nuclear errors, 46.2% for embryos with one cell affected, 27.6% for embryos with both cells affected, compared to 58.6% for mononucleated cells, p < 0.001 for both. Binucleated embryos were as likely as mononucleated embryos to become clinically useful blastocysts (56.8% vs 58.6%, n.s., unadjusted OR 0.94), whereas all the other phenotypes were less likely to develop into good quality blastocysts. The worst outcome was noted for embryos with split nucleation, with just 12.4% BFR, OR 0.12 (0-08-0.21), p < 0.001.

CONCLUSION: Nuclear errors are common at the two-cell stage. Overall, presence of nuclear errors reduces the likelihood of becoming good quality blastocysts. Both the number of affected cells and the different nuclear error phenotypes have impact on blastocyst formation rate, except binucleated embryos.

We developed an efficient approach to diagnostic copy number analysis of targeted gene panel or whole exome sequence (WES) data. Here we present CNV-Z as a new tool for detection of copy number variants (CNVs). Deletions and duplications of chromosomal regions are widely implicated in both genomic evolution and genetic disorders. However, calling CNVs from targeted or exome sequence data is challenging. In most cases, the copy number of a chromosomal region is estimated as the depth of reads mapping to a certain bin or sliding window divided by the expected number of reads derived from a set of reference samples. This approach will inevitably miss smaller CNVs on an irregular basis, and quite frequently results in a disturbing number of false positive CNVs. We developed an alternative approach to detect CNVs based on deviation from expected read depth per position, instead of region. Cautiously used, the cohort of samples in the same run will do as a reference. With appropriate filtering, given high quality DNA and a set of suitable reference samples, CNV-Z detects CNVs ranging in length from one nucleotide to an entire chromosome, with few false positives. Performance is proved by benchmarking using both in-house targeted gene panel NGS data and a publicly available NGS dataset, both sets with multiplex ligation-dependent amplification probe (MLPA) validated CNVs. The outcome shows that CNV-Z detects single- and multi-exonic CNVs with high specificity and sensitivity using different kind of NGS data. On gene level, CNV-Z shows both excellent sensitivity and specificity. Compared to competing CNV callers, CNV-Z shows higher specificity and positive predictive value for detecting exonic CNVs.

Sudden cardiac death (SCD) is a tragic and traumatic event. SCD is often associated with hereditary genetic disease and in such cases, sequencing of stored formalin fixed paraffin embedded (FFPE) tissue is often crucial in trying to find a causal genetic variant. This study was designed to compare two massive parallel sequencing assays for differences in sensitivity and precision regarding variants related to SCD in FFPE material. From eight cases of SCD where DNA from blood had been sequenced using HaloPlex, corresponding FFPE samples were collected six years later. DNA from FFPE samples were amplified using HaloPlex HS, sequenced on MiSeq, representing the first method, as well as amplified using modified Twist and sequenced on NextSeq, representing the second method. Molecular barcodes were included to distinguish artefacts from true variants. In both approaches, read coverage, uniformity and variant detection were compared using genomic DNA isolated from blood and corresponding FFPE tissue, respectively. In terms of coverage uniformity, Twist performed better than HaloPlex HS for FFPE samples. Despite higher overall coverage, amplicon-based HaloPlex technologies, both for blood and FFPE tissue, suffered from design and/or performance issues resulting in genes lacking complete coverage. Although Twist had considerably lower overall mean coverage, high uniformity resulted in equal or higher fraction of genes covered at ≥ 20X. By comparing variants found in the matched samples in a pre-defined cardiodiagnostic gene panel, HaloPlex HS for FFPE material resulted in high sensitivity, 98.0% (range 96.6-100%), and high precision, 99.9% (range 99.5-100%) for moderately fragmented samples, but suffered from reduced sensitivity (range 74.2-91.1%) in more severely fragmented samples due to lack of coverage. Twist had high sensitivity, 97.8% (range 96.8-98.7%) and high precision, 99.9% (range 99.3-100%) in all analyzed samples, including the severely fragmented samples.

OBJECTIVE: To validate a morphokinetic implantation model developed for EmbryoScope on embryos with known outcome, compared to standard morphology in a retrospective single center study.

METHODS: Morphokinetic annotation of 768 embryos with known outcome between 2013 -2015; corresponding to 116 D3 fresh embryos, 80 D6 frozen blastocysts, and 572 D5 blastocysts, fresh or frozen. The embryos were ranked by the KIDScore into five classes, KID1-5, and grouped into four classes based on standard morphology. Pregnancy rates, clinical pregnancy rates and live birth rates were compared. Combinations of morphology and morphokinetics were evaluated for implantation rates and live births.

RESULTS: Live birth rate increased with increasing KIDScore, from 19% for KID1 to 42% for KID5. Of all live births, KID5 contributed with 71%, KID4 with 20%, KID3 with 4%, KID2 with 4%, and KID1 with 2%. For morphology, the corresponding figure was 43% for Top Quality, 47% for Good Quality, 4% for Poor Quality, and 5% for Slow embryos. For day 3 embryos, KID5 embryos had the highest live birth rates, and contributed to 83% of the live births; whereas the second best morphological class had the highest live birth rate and contributed to most of the live births. For blastocysts, the KIDScore and morphology performed equally well. Combining morphology and morphokinetics indicated stronger predictive power for morphokinetics.

CONCLUSIONS: Overall, the KIDScore correlates with both implantation and live birth in our clinical setting. Compared to morphology, the KIDScore was superior for day 3 embryos, and equally good for blastocysts at predicting live births.

OBJECTIVE: Our primary aim was to compare the morphology and morphokinetics on inter- and intra-observer agreement for blastocyst with known implantation outcome. Our secondary aim was to validate the morphokinetic parameters' ability to predict pregnancy using a previous published selection algorithm, and to compare this to standard morphology assessments.

METHODS: Two embryologists made independent blinded annotations on two occasions using time-lapse images and morphology evaluations using the Gardner Schoolcraft criteria of 99 blastocysts with known implantation outcome. Inter- and intra-observer agreement was calculated and compared using the two methods. The embryos were grouped based on their morphological score, and on their morphokinetic class using a previous published selection algorithm. The implantation rates for each group was calculated and compared.

RESULTS: There was moderate agreement for morphology, with agreement on the same embryo score in 55 of 99 cases. The highest agreement rate was found for expansion grade, followed by trophectoderm and inner cell mass. Correlation with pregnancy was inconclusive. For morphokinetics, almost perfect agreement was found for early and late embryo development events, and strong agreement for day-2 and day-3 events. When applying the selection algorithm, the embryo distributions were uneven, and correlation to pregnancy was inconclusive.

CONCLUSIONS: Time-lapse annotation is consistent and accurate, but our external validation of a previously published selection algorithm was unsuccessful.