Introduction to BBMI-Omics - BBMRI-NL

Introduction to BBMI-Omics
P. Eline Slagboom
Leiden University Medical Center
BBMRI 2.0 Infrastructure connects:
Linkage to medical
socioeconomic\
registries
Communication to donors
and public
Science Communication
Maps, Atlases
Methodology
Training
Collaboration with Industry
Tissue portals
BBMRI 2.0
Infrastructure sharing
Data & Methodology
Ethical/legal Issues
Existing Biobank Data
BW/Age/menopause
Body composition
Medication Use
Lifestyle and Behavior
Health&Disease phenotypes
Omics data
GoNl DNA seq
RNA seq
DNA methylation
Metabolomics
Imaging data
BBMRI-Omics
genomic markers, biomarkers, biology
N=100,000
N=3,500
BIOS
consortium
N=2,000
BIOS
consortium
N=40,000
METABOLomics
consortium
N>250,000
Topic
Study
Migrain
LUMINA/CHARM/RVCL
Follow
Up (y) Cases
NTR VU
4.4
ERF EUMC
Dementia
VUMC Alzheimer
3
EUMC dementia
Depression
897
1000
360
1000
1100
400
1000
1000
1200
400
NTR VU
4.4
1000
1000
900
1000
All cohorts
LLS LUMC
10
998
2313
EUMC 85+
1-11
400
1200
Alpha/Omega MUMC
5.5
459
476
900
STEMI UMCG
400
UNCORBIO UMCU
3
PROSPER LUMC
3.2
418
7
145
Type 2 Diabetes CODAM MUMC
Maastricht Study MUMC
DZS West-Friesland VUMC
GARP LUMC
1200
10
1000
500
2-6
RAAK-PAPRIKA LUMC
LUMC
VU
VUMC
EUMC
UMCG
MUMC
WUR
AMC
RUMC
RIVM
2030
476
2030
Disease-specific
1000
Generic profiles
6.6
793
CHECK
8
981
LifeLines
4 -> 30 cohorts
412
EUMC OA
500 FG
579
854
HELUIS AMC
Omics
125
6
CardioVascular
Disease
BIOMArCS EUMC
Osteoarthritis
439
NESDA VU
EUMC depression
Mortality
Ageing
Controls
500
1500
BBMRI 2.0
Sharing and Steering
BBMRI 2.0 WP2 leaders
Eline Slagboom,
Dorret Boomsma
Cornelia van Duijn
Marian Beekman (coordinator)
Connection/meetings
with WP 3-6 leaders
to establish cross links
NL Cohorts
BIOS MT
Bas Heijmans
Lude Franke
Metabolomics MT
Marleen van Greevenbroek
Marije Doppenberg
Molecular variables :
‘Omics’
Epigenome
Immune
Profiling
Gut
microbiome
Integrate studies into different relationships
BBMRI-OMICS:
Warehouse of data shared and used by the community
http://www.bbmri.nl/omics/
http://www.bbmri.nl/omics/
BBMRI-Omics overview of data
Select omics data type(s) of interest
Select biobank of interest
Sample makeup of selected biobanks
Age distribution
Erik van den Akker
Make a score per individual ;
compare to traditional markers; multiple sampling Jurriaan Barkey-Wolf
1H-NMR metabolomics platform
Metabolic health ; well-standardized; 20 euro/sample
7 Diseases; 22 cohorts; 25.000 Dutch Caucasians
Ovelapping (Generic) risk profiles
Type 2
Diabetes
Cardiovascular
Disease
Osteoarthritis
Metabolome
Dementia
N=25.000
Depression
Migraine
Ageing
Mortality
Metabolomics as generic markers
M/CVD/T2D/Dep > M_HDL_C,CE,FC
M/CVD/T2D/OA > IDL_TG% + L_LDL_TG%
M/CVD/Mig/OA > PUFA/FA
M/AD/Mig/OA
> S_HDL_FC%
M/T2D/Dep/OA > S_HDL_FC, Lactate
M/T2D/Dep/Mig > FaW3/FA, ApoA1
Metabolites report on Lifestyle changes ?
GOTO (Growing Old Together)
13-weeks intervention (164 subjects) v.d. Rest et al., 2016
• 12.5% reduced dietary intake
• 12.5% increased physical activity
Baseline
Before baseline:
• FFQ
• IPAQ
• Accelerometer
• 24 hr blood glucose
End
During intervention
• 4 x 24h recalls
• Diary
• Hunger and satiety
questionnaires
One week before end:
• Accelerometer
• 24 hr blood glucose
Metabolomic Change after 13 weeks of lifestyle
intervention
* Independent of weight change
Wurtz 2015 Circulation; Stancacova 2012 Diabetes; Mahendran 2013 Diabetes Care
What does the Metabolome reflect:
Android trunk fat in DEXA scans
How do we collaborate
MRI
Metabolome
Genome
Medication
use
Metabolome
Metabolome
Central
communication
Gut
Microbiome
Metabolome
Genome
Body
Composition
Genome
With Cohorts
Joint effforts
Vouchers for
Communication
With Public
Meetings and
Trainings
Lifestyle/
Behaviour
Metabolome
Genome
Future
Longitudinal data
Exposome (observational, experimental)
Personal monitoring devices
Metabolic Phenome Centre
Netherlands
Metabolic
Phenome Centre
Subject Database
General Population
Clinical Studies
Eline Slagboom
Leiden University
Medical Centre
Metabolites in
Causal pathway
Technology Cores
Biomarkers for
Treatment
Miniaturized sample handling
& preparation
High throughput
metabolomics
Genomics, metabolomics &
patient data integration
Systems Pathology &
Systems Pharmacology
New
Treatment
Options
Pathways
to treat
Focus:
• Alzheimer and related disorders
• Vascular pathology
• Aging and longevity
• To be extended – do join the team!
Phenotypic
screening of
in-vitro models
Cornelia van Duijn
Erasmus MC