2018 12-07 Danone-Nutricia Precision Nutrition Forum, Utrecht, Alain van Gool

Innovations towards
Personalized Health(care)
Prof Alain van Gool
Professor Personalized Healthcare
Head Translational Metabolic Laboratory
Strategic advisor of the executive board
Coordinator Radboudumc Technology Centers
Danone-Nutricia Precision Nutrition symposium
Utrecht, 6 Dec 2018

3 Alain van Gool, Danone-Nutricia Precision Nutrition symposium, Utrecht, 7 dec 2018

Exponential developments – lab technology
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1500
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m/z
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4

5
Exponential developments
- digital biomarkers
5

Exponential developments - data

Role of molecular biomarkers in Personalized Healthcare
Personalized diagnosis
Personalized therapy
= Personalized healthcare
+Patient participation
X-Omics
Therapy monitoring

Genomic impact in Personalized Health(care)
Personalized medicine:
B-RAFV600E drugs for melanoma
Personalized health:
BRCA-driven preventive surgery

Technology developments in Genomics
More and longer reads at lower costs

Diagnostic progress by Whole Exome Sequencing
Human Genetics Nijmegen (Lisenka Vissers, Marcel Nelen, Han Brunner et al)
Retrospective analysis of Intellectual Disability cohort (n=150)
Sanger sequencing
Gene-by-gene
5.4 tests / patient (1-28)
Whole Exome Sequencing
All genes at once
1 test / patient

Next: Whole Genome Sequencing
Circus plots of Whole Genome Sequences of two metastatic cancer patients
Source: prof Edwin Cuppen, Hartwig Medical Foundation

Interpretation of genetic variants gets harder
“Functional studies can be a powerful tool in
support of pathogenicity”
Richards et al., Genet Med. (2015)17:405-24
Variant classification:
1. Benign
2. Likely benign
3. Uncertain significance
4. Likely pathogenic
5. Pathogenic
Guidelines American College of Medical Genetics and Genomics (ACMG)
More sequence data =
more unknown variants

The DNA-RNA-protein-metabolite dogma
Text book
DNA
RNA
Protein
Metabolite
Reality
{Karr, Cell 2012}Environment

Complexity in protein biology
21.000 genes
1.000.000 -2.000.000
protein forms
N-Glycosylation
Truncation
Phosphorylation
Acetylation
Ubiquitination
…

Functional Omics platforms
Research Biomarkers Diagnostics
Translational Metabolic Laboratory (www.youtube.com/watch?v=yhLbuX0H7rg)
Glycopeptidomics
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Metabolomics
400
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800
1000
1200
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10 20 30 40 50 60 Time [min]
Bottom-up proteomics
Glycomics
Top-down proteomics Functional genomics

Uric acid
Human
samples
Plasma, CSF (urine)
Controls vs. patient
QTOF Mass Spectrometry
- Reverse phase liquid chromatography
- Positive and negative mode
- Features
XCMS
Alignment
Peak comparison
> 10,000 Features
Xanthine
Whole Exome Sequencing
Karlien Coene
Leo Kluijtmans
Ron Wevers
Genomics & Metabolomics

Genomics & Glycomics
SLC8A6
GlycoModelControl(n=40)
SLC10A7-CDG
(n=4)
O
therCDG
-II(n=21)
-150
-100
-50
0
50
100
P33
P32
P17
P39
Modelvalues
99 patients; 47 without known gene defect
- Glycomics profiling on 99
- Intact transferrin glycoprofiling on 99
- Whole Exome Sequencing for 32 cases
PGM1: New Eng J Med 2014
Man1B1: Brain 2014
More subtle changes: here
(manuscript in prep)
Dirk Lefeber
Monique van
Scherpenzeel

Genomics & Glycoproteomics
• Mass spectrometry analysis of glycoproteins in human plasma
• 1/20 microliter analysis: detection of 1.000.000 signals in one scan (1,4 Gb)
• ~40.000 peptides of which >80% contain sugar modification
• Potential to screen patients and identify new biomarkers?
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Proof of principle study:
Biomarkers !?
Hans Wessels, Alain van Gool, Dirk Lefeber

Functional genomics
functional validation
of variants with unknown
significance
CRISPR/Cas9
rescue
biomarkers
animal model
iPSC
+nGFP +nGFP +TAZ
contr BTH BTH
PTPS deficiency PTPS deficiency-Corr#1
TH/βIII-tubulin/DAPI
complementation
Control clpb MO
mdh1Δ
mdh1-P128L
mdh1-P202L
mdh1-G30R
hMDH2
MDH1
-
YPD
fermentation
YPD
respiration
α-actinin
α-ManNAc
CH3
β-ManNAc
CH3
2.10 2.05 2.00
{Rodenburg,
J Inherit Metab Dis, 2018}
micro-organism model
Richard Rodenburg
Omar Tutakhel

Precision medicine in genetic-metabolic disease – current
Genomics
(WES)
Metabolomics
(IEM panel)
New disease
mechanisms
Personalized therapies
Nature Genetics 2018
NEJM 2014
Nature 2016
NEJM 2014
Genet Med 2017

Precision medicine in genetic-metabolic disease - future
Genomics
(WGS)
Metabolomics
(more panels)
New personalized
therapies
Glycomics
Glycoproteomics
Deep Learning
Artificial Intelligence
System biology
Nature Genetics 2016 Pilot 2017
New disease
mechanisms

… but not all data is useful data !

3 key aspects of personalized health(care)
‘I want to stay healthy. If not, how do I get healthy?’
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?

Personalized health(care) model
Personalized
Intervention
of patients-like-me
Personal thresholds
of persons-like-me
Big
Biomarker
Data
Molecular
Non-molecular
Environment
…
Time
Disease
Health
Selfmonitoring
Adapted from Jan van der Greef, TNO
Personal profile
Personalized health
Personalized medicine

We need a personalized data-driven GPS for health
• Monitor on background
• Alert when you are at risk
• Advice what to do

Partners in personalized health(care) innovation

Moving forward from quantity to quality
innovation
1. Research to research
2. Research to diagnostics
3. Research to society

1. Focus on the end user: the patient / citizen

Need to change our focus

2. Join forces in biomarker activities
{van Gool et al, Nature Reviews Drug Discovery, Apr 2017}
COST action CA16113
http://clinimark.eu

3. Interpret a person’s data with self-normalisation
healthy disease disease +
treatment
A
treatment
100%
Normalisation of responders
C
Subgroups
B
treatment
100%
Individual data through self-monitoring
D
treatment time

4. Do realize there is no single one reflection of health
• Funhouse mirror effect
• Multiple sources of your
data
• Omics
• EPD
• Diagnostics
• Wearables
• Health apps
• Commercial health tests
• Social media
• Surrounding
• Each give an (incomplete)
image of you
• How to deal with this for
personal health?
{Mira Vegter, Hub Zwart, Alain van Gool, in prep}

5. Be open to alternative therapies
33
Precision
Pharma-NutritionPrecision
medicine
Precision
nutrition

European
nationallocal
6. Progress further through collaboration

Netherlands X-omics Initiative
• Access
• Helpdesk / training
• Collaboration

United for Metabolic Disease
• National multidisciplinary
collaboration
• Clinicians + laboratory
specialists + patients
• Step-wise focus:
1. Awareness
2. Diagnosis
3. Understanding
4. Therapies
5. Care and prevention

7. Collaboration towards nationwide programs

8. And learn from other fields!

Acknowledgements
Translational Metabolic Laboratory
Hans Wessels
Dirk Lefeber
Karlien Coene
Leo Kluijtmans
Richard Rodenburg
Jolein Gloerich
Anouk Suppers
Purva Kulkarni
Roel Tans
Esther Willems
Ron Wevers
and others
Edwin Cuppen
Albert Heck
Thomas Hankemeier
Peter Bram ‘t Hoen
Daniella Kasteel
and others
Collaborators/funders
Human Genetics Nijmegen
Marcel Nelen
Alexander Hoischen
Lisenka Vissers
Christian Gillisen
Han Brunner
and others
alain.vangool@radboudumc.nl
www.radboudumc.nl/en/people/alain-van-gool
www.slideshare.net/alainvangool
CarTarDis
Irene Keularts
Hans Scheffer
and others
Rainer Bischoff
Theo Luider
and others

2018 12-07 Danone-Nutricia Precision Nutrition Forum, Utrecht, Alain van Gool

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2018 12-07 Danone-Nutricia Precision Nutrition Forum, Utrecht, Alain van Gool