Nutrigenomics and Personalised Nutrition. John Hesketh

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1 Nutrigenomics and Personalised Nutrition How close is science-based evidence to support personalised nutrition? How best can these technical capabilities be put to use? John Hesketh Newcastle University

2 Can genome technology (nutrigenomics) be used to customise/ improve nutritional advice?

3 Dietary requirements: one size does not fit all Benefit Risk Dietary intake

4 My GP says that I have a family history of heart disease and that I should be careful with my diet, eat less fatty foods. The consultant said that I should be DNA tested for hypercholesterolaemia The nutrigenomics company says that my gene A may give me higher chance of heart disease unless I take a vitamin supplement and my gene B seems to protect against heart disease if I eat less unsaturated fats.

5 Personalised nutrition It is about Disease risk, susceptibility Health issues where genetics is only one factor Multifactorial disease Today s talk Metabolic and genetic complexity The steps from genetics to individualising nutritional requirements Problems/ Needs for development

6 Genetic, dietary and lifestyle factors all have roles in susceptibility to multi-factorial disease Lifestyle Diet Individual differences in gene expression Variation in metabolism Disease risk varies between individuals Risk modulated by a combination of diet and genetics Susceptibility to disease

7 Genetic variation Human population contains naturally occurring heritable DNA sequence variations Mostly single nucleotide polymorphisms (SNP) Different sequence alternatives occur in the normal population Huge number; ~7 million in which least frequent alternative occurs in 5% Cost of sequencing now down to hundreds Need minute sample few cells from a mouth scrape

8 Metabolic complexity

9 Large scale genomics not giving us the answer so far SNPs being identified ; Human Variome Project Genome-wide association studies (GWAS) Powerful, but need large populations Type-2-diabetes - 40 variants contribute to risk ulcerative colitis -71 LDL cholesterol Limited success only accounts for 3-10% of risk whereas up to 40% estimated to be heritable Not yet taken environmental factors (e.g. diet) into account yet Need even bigger populations Masses of data bioinformatic and statistical challenges

10 SNPs influence nutrient metabolism Polyunsaturated fatty acid (PUFA) intake modulates the effect of the 75A/G SNP on high-density lipoprotein cholesterol In GA or AA individuals increased PUFA intake were associated with higher HDL-C Opposite effect observed in G/G homozygotes. from Corella and Ordovas Annual. Rev. Nutr :341 90

11 Identification of SNPs FILTER Functionally relevant SNPs Genetic variation across pathways affected by nutrient COMBINE DATA ON MULTIPLE SNPs INTEGRATE Nutrient intake/status Inter-individual variation in metabolism RELATE TO DISEASE RISK Susceptibility to multifactorial diseases Personalised Nutrient requirements

12 Robust personalised nutrition would need complex knowledge all the genetic factors that influence metabolism, multiple SNPs across whole metabolic pathways Se ; 25 genes, so far ~8 functional SNP Folate; at least 3 functional Lipid metabolism 93 SNP in 13 genes How these factors in combination influence disease risk How these factors in combination with diet and environmental factors influence disease risk Quantify contribution of effects to risk

13 Technically possible for everyone to have their DNA sequenced, our genetics does affect response to nutrients, but. Links of many specific variants to nutrition/diet not known Genetic factors influencing metabolism of each nutrient not fully understood Food a complex mixture of nutrients Links of many specific variants to disease not known - genome-wide studies have not identified variants when diet/lifestyle factors considered

14 Future opportunities Expand screening where single or few variants involved and clearly a major factor e.g. Haemachromatosis & iron metabolism For more complex multifactorial diseases Identify the most important genetic variants that affect nutrient metabolism Use high-throughput measurements of all metabolites in blood/urine to get robust estimate of dietary intake (metabolomics) Assess how multiple variants and diet affect disease risk Develop mathematical modelling tools to quantify and predict effects of variants and nutrition Produce and validate genetic risk scores

15 Identification of SNPs FILTER Functionally relevant SNPs Genetic variation across pathways affected by nutrient COMBINE DATA ON MULTIPLE SNPs INTEGRATE Nutrient intake/status Inter-individual variation in metabolism RELATE TO DISEASE RISK Susceptibility to multifactorial diseases Personalised Nutrient requirements

16 The company Yrgen told me that my genes A And B may give me higher chance of heart disease unless I take a folate supplement but more folate may increase my affect my chances of getting cancers. My gene C seems to protect against heart disease, especially if I eat less unsaturated fats. Wow, confusing! Maybe I won t ask Yrgen to assess how my genes affect my disease risk? The assessment will make me worry and could affect my job, insurance,.

17 How can this science be best delivered? Everyone could be DNA sequenced Scientific basis needs to be as robust as clinical biochemistry Need for people trained in both genetics and nutrition? NHS GP Clinical geneticists Nutritionists/Dieticians? Private companies/ nutrigenomic consultants