Transcript Document
Personalised Nutrition
Eileen R Gibney
UCD Institute of Food and Health
www.ucd.ie/foodandhealth
2002: Institute of the Future
Palo Alto
2002: Institute of the Future
Palo Alto
“The Direct Market Will be
Sizeable…
Our conservative forecast
indicates that at least one third of
consumers will be making some
changes in their nutrient intake
in response to personalised
nutrition by 2010”.
Personalised Nutrition
Using knowledge to optimise an individuals diet
General healthy eating guidelines
Individualised dietary analysis
Phenotype (Biochemical profile)
Genetic profile
Population
dietary
advice
Clustered
dietary advice
Gene based individual
dietary advice
Genetic variation
Height
Eye Colour
Hair Colour
Nutrient requirements
Nutrient-gene examples
• Association studies:
– Linking a genetic variation to a physical trait
• FTO gene and body composition
• TAS2R38 taste receptor and food intake
• Intervention studies
– Where we can demonstrate that response to specific
interventions vary according to genotype
• Weight loss
• Salt sensitivity
• Lipid metabolism
Association studies
• Genetic variation in taste
– Influence of genotype on food choice
– TAS2R38 gene
• Genetic variation in body composition
– Influence of genotype on adiposity levels
– FTO gene
Genetic variation in TAS2R38?
Table 1- amino acids substitutions giving rise to variations
• TAS2R38
• Bitter receptor gene in FP in
tongue
• 3 SNPs polymorphisms result in
amino acid substitutions
At position 49-amino acid
encoded is either proline or
alanine
At position 262-amino acid
encoded is either alanine or
valine
At position 296-amino acid
encoded is either valine or
isoleucine
PP
AA
AA
VV
VV
II
Tasters
Non-tasters
Table 2- Taster sub-groups
PP
PA
AA
AA
AV
VV
VV
VI
II
Super
Tasters
Mediumtasters
Nontasters
TAS2R38 genetic variation
• Supertasters V Non / Medium tasters:
– More sensitive to taste of sugar
– Find fats creamier
– Detect / Bitter substances at lower levels
• Suggested effect on
– Fruit and veg intake (bitter)
– Fat intake
– Alcohol intake
• Examine effect of genetic variation on habitual food intake
(F & V) in Irish children (FIRM 2006-2010)
Feeney et al, Proc Nut Soc 2011
Anthropometry breakdown
Characteristics of participants
Children n 525
Males
n 225
Adults n 165
Females
n 300
Males
n 39
Females
n 126
Mean
S.D
Mean
S.D.
Mean
S.D.
Mean
S.D.
Age / years
10.48
1.56
10.09
1.31
45.56
6.24
39.57
9.03
Weight / kg
38.94
10.79
38.20
10.54
84.36
11.70
68.99
14.62
Height / cm
143.66
10.96
140.72
9.88
176.99
7.92
163.08
7.63
BMI / kg m-2
18.58
3.34
19.01
3.39
26.96
3.68
25.91
5.16
Feeney et al (in prep)
Significant Differences* in Food
Group Intake in Children
Genotype
Total
children
• Rice, pasta, grains & starches (NT > MT)
• Processed potato products (ST > MT & NT)
• Carrots (NT > ST)
Boys
• Rice, pasta, grains & starches (NT > MT & ST)
• Biscuits & cakes (ST > MT & NT)
Girls
*Denotes significances of p≤0.05
PROP Taster Status
• Yoghurts (NT > MT)
• Yoghurts (NT & ST > MT)
• Fish (MT > ST)
• High-calorie beverages
(ST >MT & NT)
O’Brien et al (in prep)
Dietary cluster analysis
• 2-Cluster Solution
• “High Fruit & Vegetable” and “Low Fruit & Vegetable”
• Genotype / Taster Status no influence on Cluster
Membership
• “High F&V” cluster sig. higher mean daily intakes of
many nutrients
O’Brien et al (in prep)
9 year old fat
mass via
DEXA scan
9 year old lean
mass via
DEXA scan
Intervention studies
• Examine whether responsiveness to a particular
nutrient / diet is influenced by a particular genotype
– Weight loss responsiveness
– Salt restriction
– n-3 PUFA intake
Genetic Phenotype Predicts Weight Loss Success:
The Right Diet Does Matter
Joint Conference - 50th Cardiovascular Disease
Epidemiology and Prevention - and - Nutrition, Physical
Activity and Metabolism – 2010
101 Caucasian women on one of 4 diets over one year
• Low CHO, high protein diet
• Very low carbohydrate diet
• Low fat diet
• Very low fat diet
3 genotypes were tested based on an array of genes
• Low CHO responsive genotype
• Low fat diet responsive genotype
• Balanced diet responsive genotype
Salt sensitivity
Natural variation in response of BP to changes in salt intake –
genetic variation in enzymes responsible for hypertension.
Obarzanek et al; Hypertension. 2003 Oct;42(4):459-67.
Variation according to genotype of Angiotension gene
RR of intervention versus usual care
Hunt et al; Hypertension. 1998 Sep;32(3):393-401
FP6 Lipgene study
“Lipids, genetics & the metabolic syndrome”
The Lipgene study
• 480 subjects WITH the metabolic syndrome
• 12 weeks dietary intervention
• Variation in NOS gene
SF MUF n-6 n-3
A
A
PUF PUF
A
A
16 12
6 Usua
l
8
20
6 Usua
l
Type
HSFA
HMUFA
Many pathways
Multiple enzymes in each
pathway
Multiple genetic variations in
each enzyme
Nothing works in isolation
Interaction of enzymes and
variations due to genetic
variation
Personalised dietary analysis:
A question of balance
Accuracy
Ease of use
Personalised Nutrition at UCD
• UCD Institute of Food and Health
– National Nutrition Phenotype Database
– JINGO
• (Joint Irish Nutrigenomic Organisation
www.ucd.ie/jingo/)
Joint Irish Nutrigenomics Organisation
University
College
Cork
University
College
Dublin
Trinity
College
Dublin
University
of Ulster
“Personalised Nutrition: An integrated
analysis of opportunities and challenges”
€9m 2011-2014
Coordinated by University College Dublin
22 partners
A detailed consultative scenario analysis
of potential business models
An 8 country study of consumer attitudes to
all aspects of the use of personalised
nutrition
A detailed review of available technologies
and the development of new software and
algorithms for personalised nutrition
An internet based proof-of-principle study for
all three levels of personalised nutrition in 8
centres (160/centre)
A comprehensive communication programme
to all stakeholders (web-site, podcasts,
citizens juries, workshops)
A detailed review of prevailing and upcoming
ethical and legal issues
2002: Institute of the Future
Palo Alto
“The Direct Market Will be
Sizeable…
Our conservative forecast
indicates that at least one third of
consumers will be making some
changes in their nutrient intake
in response to personalised
nutrition by 2010”.