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Medicover Genetics posters at ESHG 2022

Medicover Genetics attended the 55th edition of the largest genetics conference in Europe, European Human Genetics Conference, held in Vienna, from 11 to 14 June 2022. The main goal of the conference is to update the audience on emerging concepts, mechanisms, and technologies in human genetics, simultaneously providing a broad view of the progress made in the different areas of our discipline.

Our team of scientists presented more than 10 posters describing new findings in genetic testing in the fields of reproductive health, rare diseases and oncology. Here, we are highlighting a couple of them.

The diagnostic yield of NGS-based gene panels in epilepsy

Authors: L. Frey, A. Munzig-Schmidt, K. Mayer, S. Lippert, O. Wachter, S. Eck, J. Philippou-Massier, K. Hörtnagel, H.-G. Klein, I. Rost

Background/Objectives

We report the yield of NGS panels applied for routine diagnostics in suspected monogenic epilepsy syndromes during the years 2019-2021.

Methods

We analyzed 181 (23 adult and 158 pediatric) patients with epilepsy of unknown etiology who underwent diagnostic testing using targeted gene panels (range 3-143 genes). The pathogenicity of variants was assessed according to ACMG criteria. Diagnostic yield was determined for all individuals according to age at genetic diagnosis.

Results

Panel analysis identified pathogenic or likely pathogenic variants in 36 of 181 patients, resulting in an overall diagnostic yield of 19,9 %. The yield depended on the age of the patient at diagnosis as well as the epilepsy syndrome. The yield was highest among infants aged 6-12 months (72,7 %, 8/11) and toddlers aged 12-24 months (60 %, 9/15). Accordingly, benign familial infantile epilepsy (BFIE) exhibited the highest diagnostic yield among epilepsy syndromes (69,2 %, 9/13), followed by Dravet syndrome (50 %, 4/8). 17 different genes harbored pathogenic or likely pathogenic variants with PRRT2 (8 patients), PCDH19 (6 patients) and SCN1A (4 patients) being most frequently affected. Missense variants were the most common type contributing to diagnosis (44 %, 16/36). Frameshift variants, nonsense variants and CNVs accounted for 31 % (11/36), 14 % (5/36) and 11 % (4/36) of cases, respectively.

Conclusion

In our diagnostic setting NGS epilepsy gene panels have an overall diagnostic yield of approximately 20 %. We observed the highest probability of genetic diagnosis in infants whereas the detection rate decreased with increasing age at the time of genetic diagnosis.

Automated secondary analysis of multiple Sample Sheets in a single NGS Sequencing run

Authors: C. Kopp, S. Rath, J. Seytter, S. Eck, D. Becker

Background/Objectives

Demultiplexing and bcl-conversion of Illumina sequencers’ output is the crucial first step to analyze the sequenced data. This — often time consuming — ‘translation’ into fastQ files needs a carefully created Sample Sheet, especially if you want to fully automate the secondary analysis. Presuming you also perform different analysis — perhaps with different index lengths — in one sequencing run, this automation will get more challenging due to splitting the different analyses into several Sample Sheets.

Methods

It is hardly possible to process multiple Sample Sheets at the same time, if they are facing the data of a single sequencer run, or a limited amount of compute is available. In that case, the automation has to prioritize the Sample Sheets regarding importance in a time saving manner. Also, invalid Sample Sheets or conflicts between all Sample Sheets have to be detected ahead of demultiplexing in order to prevent running into errors during processing, or in further analyses.

Results

The script improves the processing time as well as the monitoring of a single, or multiple sequencing runs and their further processes significantly, independent of the number of their respective Sample Sheets. Additionally, the hands-on time is reduced whereas the data generation is reproducible with ease.

Conclusion

At first, Sample Sheet handling is challenging, but the time that will be saved in the future is worth implementing such a task into the routine. Furthermore, additional quality checks are implemented and can be expanded — almost — limitless.

Validation analysis of a non-invasive pre-implantation genetic test for aneuploidy (niPGT-A)

Authors: M. Blankenburg, J. Stefaniak, M. Bloechle, M. Stumm

Background/Objectives

Invasive techniques such as polar body-, blastomer-, trophectodermbiopsy or blastocentesis are used in preimplantation genetic diagnosis to obtain embryonic DNA. The finding of cell-free embryonic DNA (cfDNA) in culture media samples from blastocysts (BCM) opened new possibilities since invasive interventions on the embryo could be avoided and false findings due to mosaic constellation could be reduced.

Methods

Non-invasive PGT-A test based on MALBAC amplification, Analyses of 1. 10 genomic DNAs with known complete and partial aneuploidies diluted to single cell level, 2. 5 prenatal samples from native amniotic fluid supernatants, 3. 20 BCM samples

Results

In genomic DNAs as well as in amniotic fluid supernatants all aberrations could be confirmed. The concordance rate was 100 %. In the analysis of BCM, the cfDNA showed a complete/partial concordance rate of ~88 % with regard to the aberrant chromosomes to the corresponding DNA from biopsied TE cells.

Conclusion

The technical and analytical reliability of the analysis platform, kit and software have been tested. In the first analyses (genomic DNA and amniotic fluid), all aberrations could be reliably detected. The final aim was to determine the efficiency and concordance rate between the cfDNA from BCM samples and the DNA from TE cell biopsies of the same embryo. Our analysis results show a high level of concordance in comparison to results of TE analysis with regard to the affected chromosomes. niPGTA is a promising new method for non-invasive aneuploidy screening in the context of artificial reproductive treatment.

Evaluating validation approaches for Whole Exome Sequencing based CNV calling in a diagnostic setting

Authors: L. Lüer, S. Font-Tellado, J. Schiller, S. Eck, D. Becker

Background/Objectives

The detection of genomic rearrangements such as copy-number variants (CNV) from Next-generation sequencing (NGS) data is an attractive alternative to the time consuming and costly MLPA and aCGH. Many different tools for CNV detection from NGS data have been developed over the last years. However, the validation of the NGS based CNV calls in a clinical setting is a major challenge, due to the high portion of false-positive calls and the lack of reference material.

Methods

We set up a patient cohort based on 23 samples and used filter settings as well as parameter modification for CNV calls to achieve an accessible number of calls. Here, we aim to evaluate CNV calling performance by comparing NGS based data to various orthogonal methods.

Results

The optimal validation methods differ, depending on the validation parameter of interest. The GIAB dataset is suitable as a truth set for precision calculation while the multitude of different methods used in generating the data makes it difficult to include it in sensitivity calculation based on short-read data. On the other hand, aCGH data is too imprecise to generate viable sensitivity values and MLPA cohorts are usually too small.

Conclusion

We show that the combination of a wide variety of validation methods as a reference system made it possible to compensate for the weaknesses of the individual technologies.

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