HOW TO DEFINE GOOD BIOMARKERS OF HEALTH? Suzan Wopereis

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Amice Walsh
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1 HOW TO DEFINE GOOD BIOMARKERS OF HEALTH? Suzan Wopereis

My personal objective: identification of biomarkers of (optimal) health Biomarker Definition: a characteristic that is objectively measured and

2 My personal objective: identification of biomarkers of (optimal) health Biomarker Definition: a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or responses to an intervention {Biomarkers definition working group, 2001 }

3 Definition of (bio)markers in context of nutrition Biomarkers: biological characteristics that are measured and evaluated Measurement quality issues such as accuracy, precision, reliability, reproducibility etc. Markers in nutrition research 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

4 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 Subtle and long term effects Multiple target tissues Choice of reference Inter individual variation

5 .ability to adapt and self-manage in the face of social, physical and emotional challenges

6 The challenge concept: Study and quantification of the stress response curve Sugar Protein Fat

7 From healthy to at risk to diseased : derailing biomarkers Late biomarkers of disease/effect Early biomarkers of disease/effect Onset of disease/effect? healthy homeostasis Nutrition Challenge tests Pharma Time Van der Greef (2005)

3. Challenge test to determine resilience Innovative

research methods and tools in nutrition science to

health An approach that measures health instead of

8 3. Challenge test to determine resilience 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

9 PhenFlex challenge test: Sugar Protein Fat olein Genes Nutr (2015), 10:13

10 The physiological response to the PhenFlex challenge A Pancreatic β-cell response (insulin, C-peptide) Amino acid, glucose, fructose absorption

11 The physiological response to the PhenFlex challenge A Pancreatic α-cell response (glucagon) TG response Incretin secretion (GIP, GLP-1)

12 The physiological response to the PhenFlex challenge A Increase liver integrity enzymes (ALAT, ASAT, ALP, GGT) Increase beta-oxidation (fasting) & lipoprotein secretion (ketone bodies, cholesterol, SPM) Lipolysis (fasting) & leptin release (NEFA, glycerol, C16:0, C18:1, C18:2, MG, DG)

13 The physiological response to the PhenFlex challenge Decrease secondary messengers & neurotransmitter precursors (inositol, myo-inositol, gly, trp) A Decrease kidney related markers (creatinine, urea, Glu) Decrease muscle integrity markers (1-& 3-methylhistidine, hydroxyproline, lactate)

The physiological response to the PhenFlex challenge -1 0 1 2 A HDL & LDL cholesterol core metabolism (TCA cycle) 0 30 60

14 The physiological response to the PhenFlex challenge A HDL & LDL cholesterol core metabolism (TCA cycle) Saturated FFA & essential FFA (C12:0, C14:0, C17:0, C18:0, AA, DHA) Branched chain AA & derivatives beta-alanine

Phenotypic flexibility as biomarker of health 134 biomarkers report on challenge responses in organs

HOMA-B Blue = responding Green = not responding Back = only at fasting Liver Ketone bodies Central

GIP, GLP-1 Indole-3-proprionic acid PhenFlex challenge Matsuda index, HbA1C, HOMA-IR glucose,

measures Muscle Lactate, beta-alanine Muscle IR index Branched chain amino acids & derivatives

specific FFA MG, DG Leptin, adiponectin Estimated SCD activity C16:1 FFA Adipose IR index Kidney

15 Phenotypic flexibility as biomarker of health 134 biomarkers report on challenge responses in organs Brain Secondary messengers Trp, Tyr, Phe, Met Pancreas Disposition index C-peptide Insulin Glucagon HOMA-B Blue = responding Green = not responding Back = only at fasting Liver Ketone bodies Central metabolism ALAT, ASAT, ALP, GGT CRP TG Liver IR index Liver IS index Gut Fructose, ribulose / xylulose GIP, GLP-1 Indole-3-proprionic acid PhenFlex challenge Matsuda index, HbA1C, HOMA-IR glucose, 1,5-anhydroglucitol Glutathione ratio, uric acid, vit E mannose, ribose, glycine, pseudo uridine RQ measures Muscle Lactate, beta-alanine Muscle IR index Branched chain amino acids & derivatives 1-methylhistidine, 3-methylhistidine 4-hydroxyproline, 4-oxoproline 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, svcam PhenFlex challenge: - 75 g glucose - 60 g palm olein - 20 g protein

16 Resilience markers of health Variation in response within 100 healthy subjects with different phenotypic flexibility hrs PhenFlex challenge L-N Low Normal High N-H PhenFlex challenge hrs

17 Variation in phenotypic flexibility in healthy subjects stress N-H lipids L-N

18 Variation in phenotypic flexibility in healthy subjects Age LOW FAT% stress lipids

19 Variation in phenotypic flexibility in healthy subjects Age LOW FAT% NORMAL FAT% stress lipids

20 Variation in phenotypic flexibility in healthy subjects stress Age LOW FAT% NORMAL FAT% HIGH FAT% lipids

21 Variation in phenotypic flexibility in healthy and T2D subjects stress Age LOW FAT% NORMAL FAT% HIGH FAT% Healthy N Diabetes type 2 lipids

22 The Project Towards health claim substantiation for whole grain wheat products

23 Whole grain wheat & metabolic health

24 Study design 98 g WGW per day 24

25 PhenFlex challenge time course

26 Aim: to show improved resilience with whole grain wheat

Results on cardio-metabolic health by classic evaluation 12 wks WGW vs RW consumption does not significantly improve markers of cardio-metabolic health 27 Vascular function FMD BP AIX

27 Results on cardio-metabolic health by classic evaluation 12 wks WGW vs RW consumption does not significantly improve markers of cardio-metabolic health 27 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

28 WGW is protective against excessive TG accumulation in liver

29 Metabolic health Liver health Effect of wheat interventions on ALAT, ASAT, GGT, 3-OH-butyrate, NEFA, insulin, glucose, TG, total chol, HDL

30 Metabolic health Liver health Same at baseline for RW and WGW ALAT, ASAT, GGT, 3-OH-butyrate, NEFA, insulin, glucose, TG, total chol, HDL RW baseline WGW baseline

31 Metabolic health Liver health No effect on by Refined Wheat ALAT, ASAT, GGT, 3-OH-butyrate, NEFA, insulin, glucose, TG, total chol, HDL RW baseline RW 12 weeks

32 Metabolic health Liver health Increased by Whole Grain Wheat ALAT, ASAT, GGT, 3-OH-butyrate, NEFA, insulin, glucose, TG, total chol, HDL WGW baseline WGW 12 weeks

33 WGW improves mainly metabolic flexibility NEFA, insulin, glucose, TG*, total chol, HDL RW baseline RW 12 weeks WGW baseline WGW 12 weeks 33 RW WGW

34 WGW improves liver flexibility ALAT*, ASAT*, GGT, 3-OH-butyrate* RW baseline RW 12 weeks WGW baseline WGW 12 weeks 34 RW WGW

35 WGW modulates secretion of inflammatory markers week 12 baseline, blue line = WGW, red line = RF * * * * * * 35

36 SIGNIFICANT CHANGED INFLAMMATION INDEX p= CRP*, Il-1b*, Il-6*, Il-8*, SAA*, TNF-α* 36

37 Total cholesterol HDL Intestine absorbs nutrients after challenge glucose chylomicron Increasing Glucose level Pancreas secretes insulin upon high glucose insulin NEFA TG Homeostasis slightly distorted ALAT ASAT GGT Triglycerides β-hydroxybutyrate Cytokines BP Vascular adhesion

Total cholesterol HDL Intestine absorbs nutrients after challenge glucose chylomicron Increasing Glucose level Pancreas secretes insulin upon

38 Total cholesterol HDL Intestine absorbs nutrients after challenge glucose chylomicron Increasing Glucose level Pancreas secretes insulin upon high glucose insulin NEFA TG Homeostasis slightly restored distorted Cytokines ALAT ASAT GGT Triglycerides β-hydroxybutyrate IHTG BP Vascular adhesion

39 Overview of results based on traditional biomarkers for health benefits accepted by EFSA 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) WGW RW ~ ~ ~ ~ ~ LEGEND risk reducing ~ no effect risk increasing

41 Scoring system for candidate markers in nutrition

42 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

age and metabolic stress, which are composite

flexibility, within a healthy population.

findings from other intervention studies using

43 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.

44 EFSA PUBLIC CONSULTATION 44

45 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

46 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!

How useful is this for ISAPP 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

47 How useful is this for ISAPP 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

48 THANK YOU FOR YOUR ATTENTION

State of the Science and Technology in Personalized Nutrition The nutritional systems biology

State of the Science and Technology in Personalized Nutrition The nutritional Ben van systems Ommen biology solution in Type 2 Diabetes and Cardiovascular Desease prevention and therapy". Ben van Ommen