Embed Size (px)
DESCRIPTION
Discussed lessons learned from Biomarkers in Personalized Healthcare with the T1D community, organized by JDRF as part of the FOCIS2014 conference.
Citation preview
Biomarkers in Personalized Health(care)
Prof Alain van Gool
Head Radboud Center for Proteomics, Glycomics and Metabolomics Coordinator Radboudumc Technology Centers
Head Biomarkers in Personalized Healthcare
A changing world
JDRF-HCT-IDS conference Chicago June 25, 2014
1991-1996 1996-1998 2009-2012
1999-2007 2007-2009 2009-2011
2011-now
2011-now
2
My mixed perspectives on personalized health(care)
8 years academia (NL, UK)
(molecular mechanisms of disease)
13 years pharma (EU, USA, Asia)
(Omics, biomarkers, personalized medicine)
2.5 years applied research institute (NL, EU)
(biomarkers, personalized health)
2.5 years university medical center (NL)
(Omics, biomarkers, personalized healthcare)
A person/citizen and family man
(EU, USA, Asia)
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
A changing world: Personalized Medicine @USA
“The term "personalized medicine" is often described as providing "the
right patient with the right drug at the right dose at the right time."
More broadly, "personalized
medicine" may be thought of as the tailoring of medical treatment to the individual characteristics, needs, and
preferences of a patient during all stages of care, including prevention,
diagnosis, treatment, and follow-up.”
(FDA, october 2013)
3
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
A changing world: Personalized Medicine @Europe
European Science Foundation 30 Nov 2012
4
Innovative Medicine Initiative 8 July 2013
European Commission Horizon2020 10 Dec 2013)
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Emerging: Personalized Healthcare in a systems view
Source: Barabási 2007 NEJM 357; 4}
• People are different • Different networks and influences • Different risk factors
5
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Personalized Healthcare in a systems view
6
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Personalized Health(care) model
Ho
meo
sta
sis
A
llo
sta
sis
D
isease
Time
Disease
Health
Personalized Intervention
of patients-like-me
Big Data
Risk profiles of persons-like-me
Molecular Non-molecular Environment …
Personal profile
Selfmonitoring
Adapted from Jan van der Greef (2013)
7
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Personalized Participatory Pre-emptive
Personalized Health(care) model
Ho
meo
sta
sis
A
llo
sta
sis
D
isease
Time
Disease
Health
Personalized Intervention
of patients-like-me
Big Data
Risk profiles of persons-like-me
Molecular Non-molecular Environment …
Personal profile
Selfmonitoring
Adapted from Jan van der Greef (2013)
8
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Personalized Participatory Pre-emptive
Example personal profile-based healthcare
{Chen et al, Cell 2012, 148: 1293}
Concept:
• Selfmonitoring (n=1)
• Routine biomarkers to alert
• Omics to explain
• Early intervention
9 JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago 25th June 2014 Alain van Gool
Selfmonitoring
10
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
However …
Knowledge and Innovation gap:
1. What to measure?
2. How much should it change?
3. What should be the follow-up for me?
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Biomarker innovation gap
• Imbalance between biomarker discovery, validation and application
• Many more biomarkers discovered than available as diagnostic test
Discovery Clinical validation/confirmation
Diagnostic test
Number of biomarkers
Gap 1
Gap 2
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Some numbers
Data obtained from Thomson Reuters Integrity Biomarker Module (April 2013)
Alzheimer’s Disease
Chronic Obstructive Pulmonary Disease
Type II Diabetes Mellitis
Eg Biomarkers in time: Prostate cancer May 2011: 2,231 biomarkers Nov 2012: 6,562 biomarkers Oct 2013: 8,358 biomarkers 24 Feb 2014: 9,240 biomarkers with 28,538 biomarker uses
EU: CE marking
USA: LDT, 510(k), PMA
13
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Reasons for biomarker innovation gap
• Not one integrated pipeline of biomarker R&D
• Publication pressure towards high impact papers
• Lack of interest and funding for confirmatory biomarker studies
• Hard to organize multi-lab studies
• Biology is complex on organism level
• Data cannot be reproduced
• Bias towards extreme results
• Biomarker variability
• …
{Source: John Ioannidis, JAMA 2011}
14
{Source: Khusru Asadullah, Nat Rev Drug Disc 2011}
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Needed: open innovation in biomarker research
Standardisation, harmonisation, knowledge sharing needed in:
1. Assay development
2. Clinical validation
Shared knowledge, technologies
and objectives
15
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
16
Good example of multi-laboratory biomarker validation
16
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
And then … Translation to personalized action !
17
Personal profile data
Knowledge
Understanding
Decision
Action
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Systems view on metabolic health and disease β-cell Pathology
gluc Risk factor
{Source: Ben van Ommen, TNO}
Visceral
adiposity
LDL elevated
Glucose toxicity
Fatty liver
Gut
inflammation
endothelial
inflammation
systemic
Insulin resistance
Systemic
inflammation
Hepatic IR
Adipose IR
Muscle metabolic
inflexibility
adipose
inflammation
Microvascular
damage
Myocardial
infactions
Heart
failure
Cardiac
dysfunction
Brain
disorders
Nephropathy
Atherosclerosis
β-cell failure
High cholesterol
High glucose
Hypertension
dyslipidemia
ectopic
lipid overload
Hepatic
inflammation
Stroke
IBD
fibrosis
Retinopathy
Chronic Stress Disruption
circadian rhythm
Parasympathetic
tone
Sympathetic
arousal
Gut
activity
Inflammatory
response
Adrenalin
Heart rate Heart rate
variability
High cortisol
α-amylase
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
Systems view on metabolic health and disease β-cell Pathology
gluc Risk factor
{Source: Ben van Ommen, TNO}
Visceral
adiposity
LDL elevated
Glucose toxicity
Fatty liver
Gut
inflammation
endothelial
inflammation
systemic
Insulin resistance
Systemic
inflammation
Hepatic IR
Adipose IR
Muscle metabolic
inflexibility
adipose
inflammation
Microvascular
damage
Myocardial
infactions
Heart
failure
Cardiac
dysfunction
Brain
disorders
Nephropathy
Atherosclerosis
β-cell failure
High cholesterol
High glucose
Hypertension
dyslipidemia
ectopic
lipid overload
Hepatic
inflammation
Stroke
IBD
fibrosis
Retinopathy
Chronic Stress Disruption
circadian rhythm
Parasympathetic
tone
Sympathetic
arousal
Gut
activity
Inflammatory
response
Adrenalin
Heart rate Heart rate
variability
High cortisol
α-amylase
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
{Nakatsuji, Metabolism 2009}
Systems view on metabolic health and disease β-cell Pathology
gluc Risk factor
{Source: Ben van Ommen, TNO}
therapy
Visceral
adiposity
LDL elevated
Glucose toxicity
Fatty liver
Gut
inflammation
endothelial
inflammation
systemic
Insulin resistance
Systemic
inflammation
Hepatic IR
Adipose IR
Muscle metabolic
inflexibility
adipose
inflammation
Microvascular
damage
Myocardial
infactions
Heart
failure
Cardiac
dysfunction
Brain
disorders
Nephropathy
Atherosclerosis
β-cell failure
High cholesterol
High glucose
Hypertension
dyslipidemia
ectopic
lipid overload
Hepatic
inflammation
Stroke
IBD
fibrosis
Retinopathy
Physical inactivity Caloric excess
Chronic Stress Disruption
circadian rhythm
Parasympathetic
tone
Sympathetic
arousal
Worrying
Hurrying
Endorphins Gut
activity Sweet & fat foods
Sleep disturbance
Inflammatory
response
Adrenalin
Fear
Challenge
stress
Heart rate Heart rate
variability
High cortisol
α-amylase
Lipids, alcohol, fructose
Carnitine, choline
Stannols, fibre
Low glycemic index
Epicathechins
Anthocyanins
Soy
Quercetin, Se, Zn, …
Metformin
Vioxx
Salicylate
LXR agonist
Fenofibrate Rosiglitazone
Pioglitazone
Sitagliptin
Glibenclamide
Atorvastatin
Omega3-fatty acids
Pharma
Nutrition Lifestyle
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
EC DG for Research and Innovation
Alain van Gool
Brussels, 11 Sept 2012
Relating tissue pharmacology – biomarker - therapy
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
Translating knowledge to field labs
1. Implementation-plan ‘Personalized diagnosis of (pre)diabetic and their lifestyle treatment in Dutch Health care’.
2. Use of Oral Glucose Tolerance Test as a stratification biomarker for (pre)diabetic patients
3. Advice a tailored treatment (lifestyle and/or medical)
4. Monitor added value of stratification
5. Communicate results and lessons learned
Being implemented in 1st line care (region Hillegom, Netherlands)
Alliance “Expedition Sustainable Care,
starting with diabetes”
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
Personalized interventions by Pharma-Nutrition
23
Open invitation to join:
• Shared Innovation Programs (pharma + nutrition + diagnostics)
• Horizon2020 public-private consortia
Higher efficacy / less side effects
JDRF symposium Biomarkers for T1D
FOCIS2014, Chicago
25th June 2014
Alain van Gool
healthy disease disease + treatment
Identify subpopulations in Personalized Healthcare
healthy disease disease + treatment
• Biomarkers in populations often have a wide range • Within this range, subpopulations can behave quite differently • Chemometric methods dealing with multiple biomarker data points are needed to
reveal such individual differences and enable personalized medicine • Leading to n=1 clinical trials
(Source: Jasper Engel, Lionel Blanchet, Udo Engelke, Ron Wevers and Lutgarde Buydens)
24
Implementing Personalized Healthcare
Stratification by multilevel diagnosis
Exchange experiences in care communities
+ Patient’s preference of treatment
People are different
25
Select personalized therapy
Personalized healthcare
My keywords to move forward:
• Participation + collaboration
• Selfmonitoring
• Personal profiles
• System biology
• (Big) Data sharing
• Personal preferences
• Personalized therapies
• Lifestyle + Nutrition + Pharma
26
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Acknowledgements
Bas Kremer
Peter van Dijken
Lars Verschuren
Jan van der Greef
Ben van Ommen
Ton Rullmann
Marijana Radonjic
Thomas Kelder
Robert Kleemann
Suzan Wopereis
William van Dongen
and others
Ron Wevers
Jolein Gloerich
Hans Wessels
Dirk Lefeber
Monique Scherpenzeel
Leo Kluijtmans
Udo Engelke
Ulrich Brandt
Lucien Engelen
and others
Lutgarde Buydens
Jasper Engel
Lionel Blanchet
Jeroen Jansen
and others
Radboud umc Personalized Healthcare Taskforce:
Paul Smits, Andrea Evers, Alain van Gool, Maroeska Rovers,
Joris Veltman, Jan Kremer, Bas Bloem, Jack Schalken, Gerdi
Egberink, Nathalie Bovy, Bob de Jonge, Viola Peulen, Marcel
Wortel, Martijn Hoogboom, Martijn Gerretsen
www.linkedIn.com
And external collaborators
27
JDRF symposium Biomarkers for T1D FOCIS2014, Chicago
25th June 2014 Alain van Gool
Example: glycoproteomics in rare diseases
28
• 12 families with liver disease and dilated cardiomyopathy (5-20 years)
• Initial clinical assessment didn’t yield clear cause of symptoms
• Specific sugar loss of serum transferrin identified via glycoproteomics
{Tegtmeyer et al, NEJM 370;6: 533 (2014)}
ChipCube-LC- Q-tof MS
• Outcome 1: Explanation of disease
• Outcome 2: Dietary intervention as succesful personalized therapy
• Outcome 3: Glycoprofile transferrin applied as diagnostic test
• Genetic defect in glycosylation enzyme (PGM1) identified via exome sequencing
