Molecular phenotyping of MCA/ID patients to improve diagnosis

Many patients with Multiple Congenital Abnormalities and Intellectual
Disability (MCA/ID) remain undiagnosed in the current clinical setting. MCA/ID
patients often have complex structural genome variation as a pathogenic cause.
Is has been shown that MCA/ID patients have a high burden of genomic imbalance
through Copy Number Variations (CNVs) (Girirajan et al. Plos Genetics 2011).
However, structural variation can also be balanced and these cases cannot be
detected using standard arrayCGH and WES methods (Gilissen et al., Nature
2014). In addition, it is difficult to reliably identify pathogenic mechanisms
in these patients since there are many genes involved in these complex
structural variation cases. Genomic rearrangements can lead to misexpression of
certain genes or can lead to changes in the non-coding portion of the genome
(e.g. Promoters/enhancers, see van Heesch et al., Cell Reports 2014). The
current diagnostic pipeline does not generate or support this type of data
analysis. Using an data-integrative approach consisting of Whole-Genome
Sequencing, RNA-Seq and ChIP-Seq we hope to increase the diagnosis rate of
MCA/ID patients with complex SV and identify pathogenic mechanisms in this
patient group.

- Using "Molecular Phenotyping" to increase diagnosis rate of MCA/ID patients
with complex SV's

- Discovery of pathogenic mechanisms and novel disease-associated genes in
MCA/ID patients.

With "molecular phenotyping" we will use a combination of Whole-Genome
Sequencing, RNA-Seq and ChIP-Seq/ATAC-Seq to better identify pathogenic
mechanisms and increase diagnosis of the MCA/ID patient group. Trio-based WGS
will be used to better identify genome variation in these patients. RNA-Seq
will allow us to look for gene-expression changes on a genome-wide level
between parents and patient. ChIP-Seq and ATAC-Seq for chromatin conformation
capture (e.g.active enhancers) will allow us to chart the changes in the
epigenomic landscape of promoters and enhancers between patient and parents.
This integrative "Multi-Omics" data gathering approach will allow us to better
zoom in on candidate pathogenic regions in this patientgroup, hence
contributing to both an increased diagnosis rate and the etiology of MCA/ID.

- Selection of MCA/ID patients without clear diagnosis through the regular
diagnostic pipeline from the division of Medical Genetics UMCU (also see Study
population section below).
- 6 ml peripheral blood sampling from patient and 20 ml of the parents.
- Isolation of PMBCs from blood for DNA, RNA and ChIP-Seq/ATAC-Seq.
- DNA isolation and Next Generation of Whole-Genome Sequencing on Illumina X10
platform.
- mRNA isolation (polyA-enriched mRNA) and RNA-sequencing on Illumina NextSeq
platform (Utrecht Sequencing Facility).
- Chromatin isolation and immunoprecipitation for H3K4me3 (active promoters)
and H3K27ac (active enhancers), ChIP-Seq of Chromatin-bound DNA on NextSeq
platform.
- Data mapping and analysis in collaboration with the Bioinformatics team of
the Cuppen group (Dr. Ies Nijman, Dr. Joep de Ligt, Sander Boymans)
- Identification of possible pathogenic events from this integrated genomic
landscape dataset
- Reporting of findings in peer-reviewed journals. In specific cases:
communication of results to the diagnostic team of clinical Genetics if the
findings aid diagnosis.

The only invasive procedure will be a venapuction for peripheral blood. The
risk of this routine procedure is minimal. See section E for more details.