Christian Gilissen PhD

Christian Gilissen associate professor

Christian Gilissen studied computer sciences at the Radboud University Nijmegen after which he started his PhD in 2006 at the department of Human genetics of the Radboud University Medical Hospital in Nijmegen under the supervision of Prof. Dr. Ir. Joris Veltman and Prof. Dr. Han Brunner. He obtained his PhD in 2012 on “Disease gene identification through Next Generation Sequencing”, for which he received the Dutch bioinformatics young researcher award. After his PhD he continued his work in Nijmegen as a post-doctoral researcher and worked for 3 months at the Computational Biology Group at the Charité-Universitätsmedizin Berlin, under supervision of Prof. Peter Robinson. In 2013 he received a personal Veni grant from the Dutch Organization for Scientific Research to develop novel methodologies based on normal variation in order to predict gene function and the impact of mutations. At the European Society of Human genetics meeting in 2014 he received the international Isabelle Oberlé award for his work on genome sequencing of patients with intellectual disability that was published in Nature. His work was also rewarded by the young investigator award of the Dutch Society of Human Genetics in that same year. From 2017 onwards he became the head of bioinformatics within the division of genome diagnostics and an associate professorship in the division of within the department of Human Genetics in Nijmegen. His most recent work involved the large-scale analyses of patients with intellectual disabilities and the characterization of genome-wide de novo mutations. In June 2017 he obtained a prestigious Vidi research grant  on the integration of exome sequencing and metabolomics. His work has been published in high-impact journals such as Nature genetics, Nature Neuroscience, American Journal of Human Genetics and others.

Additional functions

Past:

• Member of the Scientific program committee of the American Society of Human Genetics (ASHG)

Current:

• Head of bioinformatics Genome Diagnostics Nijmegen and Maastricht UMC
• Chairman FWO panel med2 for personal PhD and post-doc grants
• Member of the Scientific program committee of the European Society of Human Genetics (ESHG)
• Member of the NWO Veni committee

Projects

Integrating Metabolomics and Genomics for understanding human Disease" (Vidi project)

The computational integration of large biomedical datasets allows the identification of biologically and clinically meaningful patterns that are otherwise not detectable. Work done in my group over the last 5 years has contributed new approaches and methods to identify disease-causing genes from large-scale genomics data and now allow clinicians worldwide to routinely identify disease-causing DNA variants among the overwhelming amount of normal variation present in any patient. However, genetics approaches provide a diagnosis in only 50-60% of patients and contribute limited knowledge to the underlying disease mechanisms. High-throughput untargeted metabolomics profiling (UMP) is now feasible and provides a complimentary and completely new perspective on the functional effects of genetic variation.
 
I will firstly develop bioinformatics analysis pipelines and statistical methods for the large-scale interpretation of the highly complex patterns that are generated by UMP. Secondly, I will integrate UMP results with those from genomics data into a “functional genomics” approach that is unique and applicable to the large-scale patient datasets currently being generated in my host institute and elsewhere. Thirdly, I will apply these methods using intellectual disabilities (ID) as a model disease where I aim to:
 
(1) Identify novel genetic causes of disease and improve patient diagnostics
(2) Gain insights into the biology underlying ID and identify novel biomarkers
(3) Pioneer novel approaches to the interpretation of non-coding genome variation
 
If successful, this project will create a functional genomics paradigm that is applicable to genomics disease testing across a wide range of genetic diseases.
 

A holistic approach to the analysis of genetic variation in patients

Next Generation Sequencing (NGS) technologies have enabled large-scale DNA sequencing projects of patient cohorts. The very large number of rare variants present in every individual’s genome has made the interpretation of genomic variation the main obstacle in identifying the genetic cause of disease. Current bioinformatic tools that predict the effect of variants are not sensitive enough to identify a single cause of disease amongst all of these rare variants. As a side-effect of large sequencing studies, information about many benign variants has become available. We and others have shown that this `normal’ variation occurring within the healthy population can be used to characterize genes based on the number and types of benign variants that a gene can tolerate. Genes with low amounts of normal variation apparently are less tolerant and more likely involved in disease. Here we propose to generalize this approach by modeling benign genomic variation that occurs within the normal population onto protein 3D structures.  From this we will identify protein substructures (domains) that are tolerant to genetic variation and therefore less important for normal protein function. We hypothesize that the pathogenicity of a novel genomic variant in such a substructure can be estimated from the presence/absence of benign variants in that substructure. This is a completely novel way of predicting the functional impact of variants that will provide information complimentary to existing methods, and will lead to high-quality predictions for many hitherto hard to analyse mutations. We will immediately apply our predictions in the routine diagnostics exome workflow to improve patient diagnosis, but also in ongoing research projects for the identification of novel disease genes. This project is based on the unusual collaboration of two distinct fields of research, protein modelling and human genetics and we believe that this unique combination will results in a better mutual understanding, an exchange of ideas and novel research, and ultimately better (personalized) healthcare.
 

Grants

• Dutch science foundation (NWO) Vidi grant “Integrating Metabolomics and Genomics for understanding human Disease". €800,000 (10/2017 - 10/2022)
• Junior Principle Investigator, Radboud UMC. €150,000 (05/2015 – 05/2018)
• RIMLS PhD grant “A holistic approach to the analysis of genetic variation in patients". €250,000 (09/2015 – 09/2018)
• Province of Gelderland, Robust investment impulse", “Compute infrastructure for Clinical genome sequencing”. €1,845,000 (03/2014)
• Dutch science foundation (NWO) Veni grant “Population variation for genome interpretation". €250,000 (01/2014 – 03/2017)
• ZONMW Technology hotel grant: “Uncovering hidden genetic variation in the human genome.” € 30,000 (01-01-2018 – 01-01-2019)

In the news

BNR interview about finding 10 new genes (publication 1 on the list key publications):

http://www.bnr.nl/radio/wetenschap-vandaag/10308899/met-statistiek-nieuwe-genen-ontdekken
http://www.medicalfacts.nl/2016/08/02/slimme-bioinformatica-levert-tien-nieuwe-genen-verstandelijke-beperking-op/
 

About publication 2 on the list (NL):

http://www.bnr.nl/player/archief/20160621185230300
http://www.kennislink.nl/publicaties/vaders-en-moeders-geven-verschillende-mutaties-door
 

About publication 5 on the list (EN):

https://www.sciencedaily.com/releases/2015/06/150606204102.htm
 

Science webinar (EN):

http://webinar.sciencemag.org/webinar/archive/exome-sequencing-today%E2%80%99s-lab
 

Interview for computer science education(NL):