HOW TO DEFINE GOOD BIOMARKERS OF HEALTH?
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HOW TO DEFINE GOOD BIOMARKERS OF HEALTH? Suzan Wopereis
Transcript of HOW TO DEFINE GOOD BIOMARKERS OF HEALTH?
HOW TO DEFINE GOOD BIOMARKERS OF
HEALTH?
Suzan Wopereis
{Biomarkers definition working group, 2001 }
Biomarker Definition:
‘a characteristic that is objectively measured and evaluated as an indicator of
normal biological processes, pathogenic processes, or responses to an
intervention’
My personal objective:
identification of biomarkers of (optimal) health
Biomarkers: biological characteristics
that are measured and evaluated
Measurement quality issues such as
accuracy, precision, reliability,
reproducibility etc.
Risk factors: variables that are related
to an increased probability of
developing a disease or injury
biomarkers & social & environmental
factors
Endpoints: clinical outcomes or
events. Surrogate markers are
substitutes for clinically meaningful
endpoints. Not all biomarkers predict
risk or function as endpoint
Markers in nutrition research
Definition of (bio)markers in context of nutrition
Why is it so difficult to quantify health effects from food/nutrition?
Free living subjects, compliance
Target population is healthy Interaction between nutrients
Multiple mechanisms
Choice of reference
Inter individual variation
Subtle and long term effects
Multiple target tissues
….ability to adapt and self-managein the face of social, physical and emotional challenges
The challenge concept:
Study and quantification of the stress response curve
Fat
SugarProtein
From “healthy” to “at risk” to “diseased”:
derailing biomarkers
“healthy”
homeostasis
Time
Onset of
disease/effect?
Early biomarkers
of disease/effect
Late biomarkers
of disease/effect
Van der Greef (2005)
Pharma
Nutrition Challenge tests
Innovative scientific approach that aims to develop standardised research
methods and tools in nutrition science to substantiate subtle effects of
food and nutrition on health
An approach that measures health instead of disease
Based on:
1. New definition of health
2. System biology based biomarkers
3. Challenge test to determine resilience
olein
Genes Nutr (2015), 10:13
PhenFlex challenge test:
Fat
SugarProtein
Pancreatic β-cell response (insulin, C-peptide)
Amino acid, glucose, fructose absorption
The physiological response to
the PhenFlex challenge
0 30 60 120 240 360 480
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
A
Incretin secretion (GIP, GLP-1)
Pancreatic α-cell response (glucagon)
TG response 0 30 60 120 240 360 480
-2-1
01
2
A
The physiological response to
the PhenFlex challenge
0 30 60 120 240 360 480
-10
12
A
Increase liver integrity enzymes (ALAT, ASAT, ALP, GGT)
Lipolysis (fasting) & leptin release
(NEFA, glycerol, C16:0, C18:1, C18:2, MG, DG)
Increase beta-oxidation (fasting) & lipoprotein secretion
(ketone bodies, cholesterol, SPM)
The physiological response to
the PhenFlex challenge
Decrease muscle integrity markers
(1-& 3-methylhistidine, hydroxyproline, lactate)
Decrease kidney related markers
(creatinine, urea, Glu)
Decrease secondary
messengers & neurotransmitter
precursors
(inositol, myo-inositol, gly, trp)
0 30 60 120 240 360 480
-10
12 A
The physiological response to
the PhenFlex challenge
Branched chain AA & derivatives
beta-alanine
HDL & LDL cholesterol
core metabolism (TCA cycle)
Saturated FFA & essential FFA
(C12:0, C14:0, C17:0, C18:0, AA, DHA)
0 30 60 120 240 360 480
-10
12
A
The physiological response to
the PhenFlex challenge
Phenotypic flexibility as biomarker of health
134 biomarkers report on challenge responses in organs
Brain• Secondary messengers
• Trp, Tyr, Phe, Met
Gut• Fructose, ribulose / xylulose
• GIP, GLP-1
• Indole-3-proprionic acid
Adipose tissue• Glycerol, NEFA & specific FFA
• MG, DG
• Leptin, adiponectin
• Estimated SCD activity
• C16:1 FFA
• Adipose IR index
Kidney• Creatinin
• Asp, Glu, Orn, Urea
• Albumin
Vasculature• Cholesterol, HDL, LDL
• SAA, sICAM, sVCAMMuscle• Lactate, beta-alanine
• Muscle IR index
• Branched chain amino acids & derivatives
• 1-methylhistidine, 3-methylhistidine
• 4-hydroxyproline, 4-oxoproline
Liver• Ketone bodies
• Central metabolism
• ALAT, ASAT, ALP, GGT
• CRP
• TG
• Liver IR index
• Liver IS index
Pancreas• Disposition index
• C-peptide
• Insulin
• Glucagon
• HOMA-B
PhenFlex challenge• Matsuda index, HbA1C, HOMA-IR
• glucose, 1,5-anhydroglucitol
• Glutathione ratio, uric acid, vit E
• mannose, ribose, glycine, pseudo uridine
• RQ measures
Blue = responding
Green = not responding
Back = only at fasting
PhenFlex challenge:
- 75 g glucose
- 60 g palm olein
- 20 g protein
Variation in response within 100 healthy subjects
with different phenotypic flexibility
20-29
L-N30-59
Low
30-59
Normal
60-70
N-H
30-59
High
PhenFlex
challenge
hrs
PhenFlex
challenge
hrs
Resilience markers of health
Variation in phenotypic flexibility
in healthy subjects
20-29
L-N
60-70
N-H
stress
lipid
s
Based on ~160 markers
stress
lipid
s
Based on ~160 markers
Age 30-59
LOW FAT%Variation in phenotypic flexibility
in healthy subjects
stress
lipid
s
Based on ~160 markers
Age 30-59
LOW FAT%
NORMAL FAT%
Variation in phenotypic flexibility
in healthy subjects
Age 30-59
LOW FAT%
NORMAL FAT%
HIGH FAT%
stress
lipid
s
Based on ~160 markers
Variation in phenotypic flexibility
in healthy subjects
Age 30-59
LOW FAT%
NORMAL FAT%
HIGH FAT%
Healthy 30-59 N
Diabetes type 2
stress
lipid
s
Variation in phenotypic flexibility
in healthy and T2D subjects
Towards health claim substantiation for whole grain wheat products
The Project
Whole grain wheat & metabolic health
PhenFlex challenge time course
Results on cardio-metabolic health by ‘classic’ evaluation
Vascular function
• FMD
• BP
• AIX
Biomarkers of vascular health
• vascular cytokines (fasting)
• homocysteine
• Magnesium (urine)
Metabolic parameters
• total, HDL, LDL cholesterol (fasting)
• TG (fasting)
• glucose, insulin (fasting)
• HbA1c
12 wks WGW vs RW consumption does not significantly improve
markers of cardio-metabolic health
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WGW is protective against excessive TG accumulation in liver
Effect of wheat interventions on
ALAT, ASAT, GGT,
3-OH-butyrate, NEFA,
insulin, glucose, TG,
total chol, HDLM
eta
bo
lic h
ea
lth
Liver health
Same at baseline for RW and WGW
RW baseline
WGW baseline
ALAT, ASAT, GGT,
3-OH-butyrate, NEFA,
insulin, glucose, TG,
total chol, HDLM
eta
bo
lic h
ea
lth
Liver health
No effect on by Refined Wheat
RW baseline
RW 12 weeks
ALAT, ASAT, GGT,
3-OH-butyrate, NEFA,
insulin, glucose, TG,
total chol, HDLM
eta
bo
lic h
ea
lth
Liver health
Increased by Whole Grain Wheat
WGW baseline
WGW 12 weeks
ALAT, ASAT, GGT,
3-OH-butyrate, NEFA,
insulin, glucose, TG,
total chol, HDLM
eta
bo
lic h
ea
lth
Liver health
WGW improves mainly metabolic flexibility
NEFA, insulin, glucose,
TG*, total chol, HDL WGW baseline
WGW 12 weeks
RW baseline
RW 12 weeks
WGWRW33
WGW improves liver flexibility
ALAT*, ASAT*, GGT,
3-OH-butyrate* WGW baseline
WGW 12 weeks
RW baseline
RW 12 weeks
WGWRW34
WGW modulates secretion of inflammatory markers week 12 – baseline, blue line = WGW, red line = RF
* * *
* * *
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SIGNIFICANT CHANGED INFLAMMATION INDEX
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p=0.0215
CRP*, Il-1b*, Il-6*,
Il-8*, SAA*, TNF-α*
Increasing
Glucose level
Homeostasis
slightly distorted
Intestine absorbs
nutrients after challenge Pancreas secretes
insulin upon high
glucose
glucose
NEFA
chylomicron
TG
ALAT
ASAT
Triglycerides
β-hydroxybutyrate
Cytokines
Total cholesterol
HDL
GGT
BP
Vascular adhesion
insulin
Increasing
Glucose level
Homeostasis
slightly distorted
Intestine absorbs
nutrients after challenge Pancreas secretes
insulin upon high
glucose
glucose
NEFA
chylomicron
TG
ALAT
ASAT
Triglycerides
Cytokines
Total cholesterol
HDL
GGT
BP
Vascular adhesion
insulin
β-hydroxybutyrate
↓ IHTG ↓↓
↓
↓↑
Homeostasis
restored
Overview of results based on traditional biomarkers
for health benefits accepted by EFSA
WGW RW
Glucose metabolism
(Glc, Ins, HbA1c, indices)
~ ~
Liver health
(MRI, ALAT)
↓ ↑↑
Cardiovascular disease markers
(total chol, LDL-chol, HDL-chol, chol ratio,
ox-LDL, TG, FMD, BP, homocysteine)
~ ~
Inflammation markers
(cytokines)
↓↓ ↑
Metabolic Resilience
(Glc, Ins, TG, total chol, HDL-chol)
↓↓ ~
LEGEND
↓ risk reducing
~ no effect
↑ risk increasing
Scoring system for candidate markers in nutrition
‘metabolic resilience’ evaluated by EFSA experts
A scientific rationale has to be provided that defines resilience as a specific body function, and
why improvement of resilience should be considered a beneficial physiological effect.
Why ‘metabolism’ and their response to a dietary challenge, is a specific body function that may
be improved, e.g. variability with age, health status.
Provide an explanation why the combined biomarker concept is an appropriate measure of
resilience.
It must be capable of being assessed in vivo in humans by generally accepted methods (EFSA
2016)
The proposed method of measurement of resilience (e.g. differential responses to a standardized
OPGLTT as measured by the extent of disruption and rate of response of selected blood markers)
should be provided, including a scientific rationale for why it is appropriate.
why the body function is best described by a number of outcome variables which are interrelated
(e.g. different markers), and which in combination could provide information about the function
how changes in serum/plasma levels of these markers, individually and collectively, reflect
changes in ‘metabolism’
At least shown in additional 2 independent studies
To demonstrate that a healthy or optimal diet in an intervention study can
improve “metabolic age” and “metabolic stress”, which are composite
biomarkers by quantifying phenotypic flexibility, within a healthy population.
These composite markers validate previous findings from other intervention
studies using phenotypic flexibility and could be the next generation
biomarkers.
EFSA PUBLIC CONSULTATION
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RESILIENCE AND MICROBIOTA
Take home message
For diagnosis of health effects of nutrition we need resilience markers of health rather than
biomarkers of disease
These are “multi-biomarker” panels representing defined and accepted health-related
processes, that can be modulated with the new PhenFlex challenge test
The PhenFlex challenge discriminates between different states of health
A 12 weeks intervention of whole grain wheat
improves metabolic resilience and metabolic stress
These resilience markers should be
validated to determine their relevance
In this way we can quantify subtle
health effects of nutrition!
These markers can also be used for substantiating metabolic health effects of
pre- and probiotics that improve metabolic health
The PhenFlex challenge can be extended to also focus more specifically on
gut health and gut function (to be discussed in discussion group “Identifying
biomarkers linking the composition and function of the microbiome to health
status”)
TNO would be interested to deliver a showcase that quantification of resilience
has added value for pre- and probiotica field.
Interested? Please contact me or Edwin Abeln
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