Host Institution

Peak Nutrition for Metabolic Health PANaMAH

Science Symposium_13th April 2016

1Prof Sally Poppitt (PI), 2Dr Karl Fraser, 1Dr Justin O’Sullivan, 3Dr John Ingram, 1Prof Garth Cooper, 1Dr Rinki Murphy, 1A/Prof Lindsay Plank, 4Dr Greg Jones & team

1University of Auckland, 2Ag Research, 3Plant & Food Research, 4University of Otago

PANaMAH team: NZ & worldwide

A/Prof Greg Jones

Prof Sally Poppitt Dr Ivana Sequiera Louise WeiWei Lu

Wilson Yip, PhD student Dr Rinki Murphy

A/Prof Lindsay Plank

Dr Justin O’Sullivan Tayada Fadason, PhD student

Dr John Ingram PhD student

Dr Karl Fraser Research Assistant

Emily Yee, PhD student Prof Garth Cooper CADET, UK; Hong

Kong; China

Prof Jean-Charles Martin INSERM, Fr

A/Prof Jun Lu

PREVIEW European Union

Focus on obesity and metabolic health in HVN is no surprise…

What are its consequences?

But perhaps a surprise that the transition has happened so quickly, particularly in Asia….

Prof. Majid Ezzati leading the NCD risk factor collaboration

Prof. Majid Ezzati leading the NCD risk factor collaboration

The obesity wave, or tsunami

• Asia is not immune – and facing an EPIDEMIC OF OBESITY as lifestyles change and the population ages

• With China confirmed as the largest global burden o 30% of adults are overweight or obese [400 million = 1/5 of the world’s obesity problem] o Leading to a tsunami of metabolic health problems

• “Paying the price for those extra pounds”

Globally, OVERWEIGHT AND OBESITY approaching 2 BILLION and rising

Globally, TYPE 2 DIABETES approaching 700 MILLION and also rising

• Asia is leading the charge – as lifestyles change, the population ages, and

people gain weight [with China confirmed as the largest global burden]

Asians are at far greater risk of poor metabolic health than their Caucasian counterparts – both at a younger age, and

lower body weight

1WHO, http://www.who.int/mediacentre/factsheets/fs312/en/2015

CONUNDRUM for 2016!

Asian Chinese are much thinner than their US counterparts YET have higher rates both of Diabetes (11.6%)

& pre-Diabetes (estimated ~50%)

http://www.smithstreetchina.com/content_index/m_healthcare.html

And hence Consumers are looking for foods that aid better metabolic health………….

KEY SCIENCE QUESTION: WHY ARE SOME PEOPLE MORE SUSCEPTIBLE [EG. ASIAN] YET OTHERS MORE RESILIENT [EG. CAUCASIAN]?

i. FAT STORAGE [ADIPOSE DEPOSITION] MAY BE AT THE ROOT OF THE

PROBLEM • the TOFI profile = lipid ‘overspill’ • are there early risk markers

ii. CAN WE TARGET THE CAUSE OF THE PROBLEM (failure of the pancreas), AND NOT JUST THE CONSEQUENCES (eg. glucose and insulin)

PEAK NUTRITION FOR METABOLIC HEALTH

And how can we best utilise this knowledge

to develop nutrition (F&B) solutions? CONSUMER NEED/BENEFIT: new foods that help maintain better glucose control prevent type 2 diabetes promote heart health

Nutrition problem = Nutrition solution

KEY SCIENCE QUESTION: WHY ARE SOME PEOPLE MORE SUSCEPTIBLE [ASIAN] YET OTHERS MORE RESILIENT [CAUCASIAN]?

1. FAT DEPOSITION MAY BE AT THE ROOT OF THE PROBLEM

• the TOFI profile = lipid ‘overspill’ • are there early risk markers amenable to F&B intervention?

2. CAN WE TARGET THE CAUSE OF THE PROBLEM (eg. failure of the pancreas), AND NOT JUST THE CONSEQUENCES (eg. high blood glucose) • through dietary (F&B) intervention

PEAK NUTRITION FOR METABOLIC HEALTH

2015 2016 2017 2019

Timeline

What is the TOFI profile and why is it important?

TOFI Thin on the Outside Fat on the Inside

Whilst obesity is strongly associated with poor glucose control & diabetes it may not just be the fat (that you can see) on the outside that’s important but also the fat on the inside

metabolically obese normal weight [MONW]

FAT ON THE INSIDE……….

Particularly fat in

the PANCREAS

from Sapanaro et al., Nutrients, 2015

We hypothesise that: Fat on the inside is more important than fat on the outside Very small amounts of fat in the pancreas (? and/or liver,

muscle, and other organs) may lead to dysregulation of glucose Asian populations may be susceptible to this lipid

‘overspill’ from adipose stores (=‘safe’ storage site) into the pancreas = TOFI; even when young & outwardly slim

This may happen long before glucose levels rise and diabetes develops

WHAT CAUSES THE LIPID ‘OVERSPILL’? = UNKNOWN There may be early biomarkers that predict ectopic lipid

storage & development of TOFI, in the blood

We hypothesise that: Fat on the inside is more important than fat on the outside Very small amounts of fat in the pancreas (? and/or liver,

muscle, and other organs) may lead to dysregulation of glucose ASIAN POPULATIONS MAY BE PARTICULARLY SUSCEPTIBLE TO THIS LIPID

‘OVERSPILL’ from adipose stores (=‘safe’ storage site) into the pancreas = TOFI; even when young & outwardly slim

This may happen long before glucose levels rise and diabetes develops

WHAT CAUSES THE LIPID ‘OVERSPILL’? = as yet UNKNOWN There may be early biomarkers in the blood that predict

ectopic lipid storage & development of TOFI

We hypothesise that: Fat on the inside is more important than fat on the outside Very small amounts of fat in the pancreas (? and/or liver,

muscle, and other organs) may lead to dysregulation of glucose Asian populations may be particularly susceptible to this

lipid ‘overspill’ from adipose stores (=‘safe’ storage site) into the pancreas = TOFI; even when young & outwardly slim

This may happen long before glucose levels rise and diabetes develops

WHAT CAUSES THE LIPID ‘OVERSPILL’? = as yet UNKNOWN… but there may be early biomarkers in the blood that

predict this ‘overspill’ & development of TOFI

SCENARIO – 2 women walk into our research clinic in Auckland…

A little overweight BMI=26kg/m2

also high glucose = ?diabetic

!!!

Why are Asian people so susceptible – even when they are lean?

Obese BMI=37kg/m2

We measure their blood glucose

Asia

n

Cau

casia

n

high glucose = ?diabetic

Exactly as we would predict

Surprisingly

Human Nutrition Unit

CONCLUSION: it’s very difficult to predict who’s at risk and who isn’t - we need better (and earlier)

markers

Glucose is a very ‘blunt’ marker of early risk

Age (y)

Weight (kg)

BMI (kg/m2)

Glucose Pancreatic fat (%)

18 52 20 normal low

25 55 21 normal HIGH

30 56 22 normal HIGH

38 58 23 HIGH HIGH

Glucose is a very ‘blunt’ marker for people without diabetes Not a good predictor of who will suddenly worsen Or when they will worsen; BUT ectopic fat probably is a good predictor and may be a very good early marker

BMI and total body fatness are not always good predictors of risk ; particularly in Asian populations who often have raised glucose even within lean range BMI

Asian Chinese

But, ectopic fat is difficult to measure Magnetic Resonance Imaging (MRI)

Not a routine clinical assessment, expensive, claustrophobic No ionising radiation, good safety profile

Pancreas

AIM: identify early blood markers of ectopic fat and poor glucose control using the

HVN METABOLOMICS PLATFORM

? Are there better early markers – metabolomics small molecules, metabolites ? Can we target these markers with F&Bs

Correlation with % pancreatic fat

small m

olecules, metabolites in circulation

? Are there better early markers – metabolomics small molecules, metabolites ? Can we target these markers with F&Bs

Correlation with % pancreatic fat

Aim: identify early blood markers of ectopic fat and poor glucose control using the

HVN METABOLOMICS PLATFORM Dr Karl Fraser, Ag Research, NZ Dr Jean-Charles Martin, INSERM, Fr

HVN Metabolomics

Hub

small m

olecules, metabolites in circulation

? Are there better early markers – metabolomics small molecules, metabolites ? Can we target these markers with F&Bs

Correlation with % pancreatic fat

Aim: identify early blood markers of ectopic fat and poor glucose control using the

HVN METABOLOMICS PLATFORM Prof Garth Cooper, CADET, U of Manchester, UK and U of Auckland, NZ [MBIE Treating Diabetes]

Visiting Professor • U of Hong Kong • Chinese Acad Sci

small m

olecules, metabolites in circulation

GLOBAL LEADER: METABOLOMICS & MET HEALTH – T2D, BRAIN/COGNITION

PANaMAH: Phase 1 Risk profile assessment

TOFI-MRI, early biomarkers

PATHWAY ANALYSIS: SMART MODELLING IN SILICO and validation studies

PANaMAH: Phase 2 Meal studies to determine food components that

(i) modulate risk biomarkers (ii) promote healthy organ structure/function (pancreas)

PRO

GRAM O

VERVIEW

Blood Tissue (bariatric cohort)

Predict foods that modulate risk profile

PANaMAH: Phase 1 Risk profile assessment

Asian & Caucasian adults: BMI 20-45kg/m2; = range of risk profiles based on plasma glucose & HbA1c

N=400+, metabolomics profile

Asian N=200, % fat DeXA

Asian

Cau- casian

N=100+, pancreatic fat, MRI

Asian Caucasian

April – Dec 2016

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FUNCTIONAL FOOD COMPONENTS – identify new interactions between foods, nutrients, bioactive components and existing & novel biomarkers of metabolic health FOOD TARGETS: Animal protein/amino acids, prebiotic oligsaccharides (eg galactoligosacharides), dietary fibre, phytochemicals BIOMARKERS: glucose regulation, insulin sensitivity (dynamic and static markers), novel predictive metabolic risk markers within proteome, metabolome, transcriptome, epigenome, liver fat, ectopic fat stores, intra-abdominal fat stores, pro-inflammatory cytokines

Smarter prediction of foods and food components that can target dysregulated pathways: • glucose, insulin • small molecules, metabolites (metabolome) • pancreas & liver….

PATHWAY ANALYSIS: SMART MODELLING – IN SILICO & VALIDN

Dr Justin Dr John O’Sullivan Ingram

PANaMAH: Phase 2 feeding studies to determine food components

that (i) modulate risk biomarkers

2017 to 2019

Dr I

vana

Seq

ueira

Lo

uise

Wei

Wei

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Wils

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PANaMAH: Phase 2 feeding studies to determine food components

that (ii) promote healthy organ structure/function

2017 to 2019

Dr I

vana

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Lo

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Wei

Wei

Lu

Wils

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Pancreas Liver

INTERDISCIPLINARY FOCUS OF: • Clinical studies • Biomarkers – validate

established & investigate novel underpinned by: • Food science • Asian consumer preferences

AIM QUICKER, CHEAPER, SMARTER

CLINICAL VALIDATION FOR REGULATORS

Key OUTPUT = Clinical Validation

HVN funding to de-risk fundamental research for Industry and provide future opportunities

You can’t do anything on your own….

Number of existing programs feeding into PANaMAH both nationally & internationally

Industry Reference Group: Incl. Zespri, Comvita, Sanitarium, Diabetic Foods Ltd

KEY PROJECTS: UoO metabolic health biobank (~10,000 NZ adults) led by A/Prof Greg Jones, SOM

Industry Reference Group: Incl. Zespri, Comvita, Sanitarium, Diabetic Foods Ltd

KEY PROJECTS: recently funded MBIE metabolic health collaboration between NZ researchers and A* in Singapore,

through the HVN Metabolomics Hub

Healthy Met Syn

Brenan Durainayagam PhD student

KEY PROJECTS: metabolomic interrogation of metabolic syndrome, in a smaller cohort of Asian Chinese and

Caucasian women [=combine datasets]

Karl Fraser

PANaMAH update: recruitment is underway for TOFI….

Caucasian Asian Chinese

Dr Ivana Sequiera, Louise WeiWei Lu, Wilson Yip PhD student