Nutritional Genomics basics for nutrition …...MTHFR 677C>T ADRB3 Trp64Arg Rs 123456 Must know...

NUTRITIONAL GENOMICS: ESSENTIAL BASICS FOR NUTRITION

PROFESSIONALS

Mariëtte Abrahams MBA RD

Course Outline

Basic Genetics

Nutrigenomics & Nutrigenetics

Personalized health era

Diet-Gene interactions in Chronic diseases

What does testing involve?

Limitations, Ethics & regulation of testing

Nutrigenetics in the marketplace – A global view

Opportunities for Dietitians

Resources & Projects

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Learning outcomes

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applies only to the educational content of this learning activity

Outline the structure and function of DNA and how it is organised in cells to form the human genome Explain what gene expression is and how environmental factors such as diet can influence gene

expression and genome function thereby influencing health and susceptibility to disease Explain what the fields of nutrigenomics, nutrigenetics and epigenetics are Demonstrate an understanding of the genetic basis of some chronic diseases Demonstrate a broad understanding of relevant genetics and genomics principles. Explain how genetic testing is conducted in practice Understand and be able to explain the limitations of gene testing Understand and explain the ethical and legal frameworks surrounding personalised health Visualise and create future opportunities where chronic disease prevention is concerned Outline relevant resources for accessing further detailed information

Part 1 – The Foundation

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What is DNA??

DNA is a long chain ofbuilding blocks (A,T,G,C)

A gene is a unit ofinformation

Genes are located onchromosomes

Every human has 46 chromosomes

All 25 000 genes in everycell

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Human Genome project

13 year project

Completed April 2003

Mapped entire human

genome sequence

Identified all genes in

human DNA

Cost $3 billion



The outcome

25 000 genes

3 Billion base pairs

99.9% of DNA is identical

0.1% variance has no functional significance

Approx Only 1-5% of DNA code for genes



Monogenetic vs Polygenetic diseases



Monogenetic disorders eg PKU

Polymorphisms are common in the

population >1%

Gene Variations

Everyone has them!

Changes in genetic information

Single Nucleotide (base change, insert,deletion)

Groups of nucleotides (repeats)

Whole chromosomes (insert, delete,rearranged)

Impact can be positive, negative or non-existent



Single Nucleotide Polymorphism (SNP)

Change in Single Nucleotidepair

Most have no direct effect onhealth

http://www.youtube.com/watch?v=9rPDa2ACtog

3-5% are functional andinfluence phenotypicdifferences (Yamada et al 2008)



http://www.youtube.com/watch?v=9rPDa2ACtog

Reading the literature



Gene name C275T

MTHFR 677C>T

ADRB3 Trp64Arg

Rs 123456

Must know nomenclature



Description

Allele A variation of a gene

Wild type, homo/heterozygote Most common version, two copies, 1 copy of each

Locus/loci An arbitrary region of the genome that can have

mutations /polymorphisms

Genotype vs Phenotype Inherited DNA vs measureable characteristics

Polymorphism Differences in DNA sequence found commonly in

>1% of population

SNP vs Genome A change in a single nucleotide/ your total sum of

DNA

Rs numbers All SNP´s are assigned a unique rs number eg rs

9939609

Mutations Differences in DNA sequence in an individual that are

rare (<1% of population) and may be unique to the

individual

Nutritional Genomics



(Stover and Caudill, 2008)

Epigenetics



“ Studies the silencing and activation of

DNA without changing the nucleotide

sequence”

What is Gene Expression?



“ The conversion of the information encoded in a

gene into mRNA and then to protein”

Gene expression

DNA codes for RNA

Moves from cell

nucleus to cytoplasm

Directs protein

synthesis



How Diet, Lifestyle & environment

impact gene expression?

Directly affect gene expression by acting as ligands for transcription factor receptors eg PUFA´s on PPAR´s

Nutrients are metabolized by primary or secondarymetabolic pathways thereby altering concentrations ofsubstrates or intermediates eg folic acid

(Fenech M et al., 2011)



Omics technologies

Transcriptomics(mRNA,micro RNA, non-coding RNA)

Metabolomics(Metabolites eg Cholesterol levels)

Proteomics(protein structures and function)



NEW NUTRITION

PARADIGM

The age of personalized health

DNA is not yourdestiny

Genotype does notmean phenotype

Tailoring treatmentand recommendationsto include genetics eg“Pharmacogenomics”



The Disease continuum



(Kauwell 2008)

How genomic technology fits in with

Nutrition



Candidate gene approach

Genome-wide linkage screen

(Lovegrove JA, Gitau R 2008)

From the old into the New

Population basedRecommendations based onRDA from observationalstudies

Adjust intake on nutritionalassessment from diet, anthro,family hx,clinical,ageand sex

General healthy eatingrecommendations or prudentguidelines for general population

Our unique DNA affects ourindividual nutrientrequirements

RDA may be based onmetabotypes or ethnic groups

Individual needs for vitamins, minerals and phytochemicals

Move from single gene-nutrient interaction to a systems biology approach



Old Paradigm New Paradigm

“One man´s food is

another man´s poison”



Quick recap!!


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activity

How it all started

Basic Genetics

What Nutritional Genomics is

How diet and lifestyle impact our Genotype andsusceptibility to develop chronic diseases

Omics Technology

Type of genetic studies

How there is a shift towards a personalized healthapproach

Part 2 – The Genes



GENES AND OBESITY

Genetic contribution to BMI



40-90% difference within individuals in a

population due to genetics (Atwood et al 2002)

32 loci explains <1.5% of variation in BMI

It is certainly not the holy grail, but only part of the

story

Four levels of genetic contribution to

Obesity

1. Genetic obesity - mutation in a single gene despite environment

(1 - 5%)

2. Strong predisposition - overweight in non-obesogenic

environment and obese in obesogenic environment

3. Slight predisposition - normal weight in non-obesogenic

environment and overweight in obesogenic environment

4. Genetically resistant - normal weight in obesogenic

environment.

(Loos and Bouchard 2003)Pomegranate Nutrition Consulting copyright 2015


GWAS identified FTO SNPs as have the most important effects on obesity susceptibility and BMI

FTO may play role in eating behaviour, satiety and dietary intake.

Rs9939609 T>A associated with higher body weight, fat mass and higher risk of obesity.

Minor allele carriers have higher intake of total energy and fat

Association was replicated in several populations

Fat mass Obesity associated gene

(FTO) T>A



FTO T>A genotype



Prevalence 46%-74% Europeans have 1 copy

18% have two copies (A allele)

51% West Africans

28-44% of Asian descent (Kalpelainen TO et al

16% Chinese

Increases risk of obesity by 30% one copy, 70% twocopies (Frayling et al., 2007)

A-allele carriers are 3kg heavier than non-carriers(Vialeswaran 2012)

Moleres et al 2012



Impact of FTO T>A gene variant

In A allele carriers high-fat diets increase obesity

susceptibility.

A allele increased obesity risk when consuming high

SAT FAT.

A allele carriers reported to consume more fat and

total energy, experience less satiety. Especially

children.

Low physical activity accentuates the susceptibility

to obesity by A allele.



Peroxisome Proliferator activated

receptor gamma (PPAR-y)

Nuclear Transcription factor

Plays a role in Adipocyte growth and differentiation

Role in Lipid and glucose metabolism

Reduced transciption related to increased regain of weight

Decreased insulin sensitivity (Masud et al., 2005)



Impact of PPAR-y gene variant

Pro12Ala C>G



CC most common version

Memisoglu et al., 2003 – Nurses health study

CC individuals particularly sensitive total amount of

fat in the diet with higher BMI

No difference in Ala carriers

MUFA intake inversely associated with BMI in Ala

carriers

Gly16Arg G>A, Gln27Glu C>G

GA 40%, AA 12%, CG 50%, GG 15%

Involved in energy expenditure regulation through

stimulating thermogenesis and lipid metabolism in adipose

tissue

Knockout mouse studies have conclusively shown that the

adrenergic receptors are necessary for diet-induced

thermogenesis, and play a critical role in the body’s

defense against obesity (Bachman et al., 2002)

Beta-2 Adrenergic Receptors (ADRB2)

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ADRB2 SNPs associated with obesity, especially

central obesity

Gln27Glu (C>G)

Glu27 (G) carriers more resistant to losing weight, lose weight slower, associated with all measures of obesity

Martinez et al. (2003) found a significant interaction between high consumption of CHO and obesity in Glu27 carriers

Gly16Arg (G>A)

Long term studies showed that weight gain from childhood to adulthood and weight gain during adulthood are higher in Gly16 allele (Ellsworth et al 2002)

Also Gly16 more resistant to weight loss and more likely to regain body weight after 6 months (Masuo et al., 2005)



dietary intake of CHO >49% E

produced an increased obesity risk in

women carrying the Glu27 allele

dietary intake of CHO >49% E associated

with higher insulin levels in women carrying

the Glu27 allele



-265 T/C (TC 47%, 10-15% CC)

Second most abundant protein of HDL particles

SNP results in 30% drop in transcription activity.

CC individuals had higher obesity risk and higher intake of total

fat and SAT FAT.

Three populations have shown a mean increase in BMI in CC

genotypes with high SAT FAT intake but not low SAT FAT intake

(Corella, 2011).

Apolipoprotein II – (APOA2)



Corella et al.,2009)



These figures clearly illustrate the benefit of including

genetics and diet in research studies

(Corella et al.,2009)Pomegranate Nutrition Consulting copyright 2015


“Subjects on Diets Appropriate for their

Genotype Achieved Statistically significant

Average Weight Loss of 6.2% of Body Weight

at one year Compared to Individuals not on a

Diet Matched to Genotype (2.4%)”-

Stanford Univ



Other areas in weight management



The Human Obesity gene map

Taste preference (TAS2R38)

Reward deficiency syndrome (DA2D)

Snacking and Binging (MC4R,CLOCK)

Appetite (LEP-R)

Obesity and Gut microbiota

Epigenetics (Barres et al 2013; Hatoum et al 2011)

Motivation and Commitment?

Personalised genotype advice improved motivation(Arkadianos et al., 2009)

Personalized advice more understandable andenjoyable to read (Nielsen and El-Sohemy, 2012)

FTO status does not impact motivation to loseweight(Jrn Gen Couns 2013, Meisel et al 2012)

http://health.usnews.com/health-news/news/articles/2013/09/06/obesity-gene-tests-may-not-hamper-weight-loss-efforts



http://health.usnews.com/health-news/news/articles/2013/09/06/obesity-gene-tests-may-not-hamper-weight-loss-efforts

What will the future be like?

GenomicKnowledge

Dieteticinput



GENES AND DIABETES

Identified in 2006

TCF7L2 gene associated with type 2 diabetes,

MetS and obesity.

Associated with increased T2D risk possibly

due to defective beta-cell functioning and

impaired insulin secretion

Operates via impaired glucagon-like peptide

1(GLP-1) secretion

Transcription Factor 7 like 2 (TCF7L-2)



Mean weight loss was -6.81 kg. All subjects no

difference between HF and LF.

CC & CT subjects no difference between HF and LF.

TT genotype weight loss was 2.57kg smaller with HF

than LF diet.

TT do better on a LF diet.


applies only to the educational content of this learning activity m

TCF7L2 C>T

During lifestyle intervention, T allele carriers

displayed lower reduction in BMI and total body

fat.

T allele requires more long term intervention to

manage weight and prevent IR and diabetes.

Need to manage QUALITY of CHO. GL & GI.

Implement all diet & lifestyle changes that will

prevent development of IR.



EPIC-interAct study (May 2014)



The absolute high risk associated with obesity at any

level of genetic risk highlights the importance of

universal rather than targetted approach to lifestyle

http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1001647

Nutrigenetics and Alzheimer´s disease



ApoE4 increases risk of CVD by 40% (Lovegrove & Gitau 2008)

25% in UK population

40% population will develop late onset AD

Diet & lifestyle intervention

REVEAL study - Impact of disclosure of APOE4 status

Genotype status did impact motivation to change(Chao et al., 2008)

Nutrigenetics and CVD



DNA cascade screening for Familial

Hypercholesterlaemia (Scotland & Wales)

LDL-R, ApoB, PCSK9

NOS-3 (Ferguson et al., 2010)

MTHFR C677T (Klerk et al., 2002)

Nutrigenetics, Epigenetics and Cancer

Cruciferous veg intake

improves detoxification

function

Contains Sulphoraphane(Ferguson and Schlothauer, 2012)

Epigenetics & polyphenols



What researchers think…..



“Dietitians and doctors can act as a reality check to Nutrigenomics, they know what goes on in the heads of their patients and clients a lot better than scientists

and can therefore bridge science and practical application”

Laura Bouwman PhD Wageningen university.

Summary



Genes play an important role in health homeostasis

Personalization may lead to improved motivation andoutcomes for chronic diseases

Specific SNP´s have been repeatedly shown to impacthealth in different populations

We don´t have all the answers in terms of gene-gene, gene-nutrient interactions, but we certainly have a starting point

Although it is early days for a nutrigenomics, in thefuture can be used as a tool as part of a effectivepersonalized nutrition intervention strategy

New nutrition research needs to integrate genomic data

Part 3 – Nutrigenetic testing



WHAT DOES TESTING

INVOLVE?

Nutrigenetic testing in the market

Weight Loss

Wellness

Sports Performance

Disease risk

Lactose Intolerance

Coeliac disease

Urine metabolites



Nutrigenetics a global view



Part 4 – Limitations, Ethics and

Regulation



LIMITATIONS OF GENE-SNP

TESTING

Limitation of DNA testing



Chronic diseases are polygenic

Contribution of single SNP to overall diseasesusceptibility usually small

Interaction between diet-genes and gene-genes (epistatis) not identified

Chronic diseases are poly-environmental

Chronic diseases are more prevalent in some ethnicgroups

Limited Biomarkers to measure impact of SNP´s

Limited standardization of testing and interpretation

Only looks at part of the genome

ETHICS OF PERSONALISED

NUTRITION

Ethical issues



Individual

Privacy

Discrimination

Psycologicalstigma

Behaviourchange

Reilly and DeBusk 2008,

Görman et al., 2012

Stewart-Knox et al.,2013

Bloss et al 2013

Ready for

practice?

REGULATORY

ENVIRONMENT

Regulation of Genetic testing



UK HGC /EU

MHRA-medical devices

US (FDA –medical devices)

Hesketh 2013

Part 5 – The Market need





Food4me project 2013

Who are Consumers and what do

they want?

HCP endorsed (Wendel et

al.,2013)

Personalized Approach if high

risk and symptomatic (Fallaize et

al., 2013)

Actionable Data

Data to be kept safe

Men and older individuals

Highly educated

More likely if result is likely to bepositive

Take preventative action

May have a relative or at at riskthemselves

(Collins et al 2013)



Where are opportunities for Dietitians?

Lead research

Genomic educators in Dietetic curriculum

Evolve public health guidelines

Lead and contribute to commercial teams

Educate public

Integrate into clinical practice

Development of functional foods



Colleen Draper,

R.deBusk

Market trends & Highlights 2014/15



23and me banned from selling personal genome test in 2013

23andme launched in the UK 2014

AND position paper on Nutritional Genomics published

First NGx sessions at both Canadian and ADA conferences

Biggest investment yet in digital health

Fitgenes, RevUP launch integrated platform

100 000 genome project gets more funding

Competency on NGx standard for UK RD´s published

BBC documentary on Personalised Nutrition aired

Resources & Projects

Food4me project (http://www.food4me.org)

Human Variome project

HAPMAP consortium

Micronutrient project

DIFM (http://integrativerd.org)

Toybox study

Qua-Li-FY

Competency Framework for Dietitians 2014

http://www.gbhealthwatch.com/healthwatch-tools.php

Diogenes

NuGO (http://www.nugo.org)

ISNN (http://www.isnn.info

NHS Genetics Education centre

http://www.geneticseducation.nhs.uk

OMIM database

AND position paper on Nutritional Genomics 2014

POUNDS-lost TRial



http://www.isnn.info/

Books



The real question…….



Where is the evidence?

vs

Where should I start?

Key messages



1 SNP does not equal chronic disease

Start Learning your special interest topics

Digital and Genomic technologies are changing ourroles

The world is moving towards prevention andpersonalisation

The Food industry is responding to consumer demandsfor more healthy and personalised foods

The field needs expert nutrition practitioners to lead, educate and get involved

THANK YOU!!!

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Individual Coaching

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Question time



References



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ATWOOD, L. D., HEARD-COSTA, N. L., CUPPLES, L. A., JAQUISH, C. E., WILSON, P. W. & D'AGOSTINO, R. B. 2002. Genomewide linkage analysis of body mass index across 28 years of the Framingham Heart Study. Am J Hum Genet, 71, 1044-50.

BACHMAN, E. S., DHILLON, H., ZHANG, C. Y., CINTI, S., BIANCO, A. C., KOBILKA, B. K. & LOWELL, B. B. 2002. betaAR signaling required for diet-induced thermogenesis and obesity resistance. Science, 297, 843-5.

CHAO, S., ROBERTS, J. S., MARTEAU, T. M., SILLIMAN, R., CUPPLES, L. A. & GREEN, R. C. 2008. Health behavior changes after genetic risk assessment for Alzheimer disease: The REVEAL Study. Alzheimer Dis Assoc Disord, 22, 94-7.

CORELLA, D., ARNETT, D. K., TSAI, M. Y., KABAGAMBE, E. K., PEACOCK, J. M., HIXSON, J. E., STRAKA, R. J., PROVINCE, M., LAI, C. Q., PARNELL, L. D., BORECKI, I. & ORDOVAS, J. M. 2007. The -256T>C polymorphism in the apolipoprotein A-II gene promoter is associated with body mass index and food intake in the genetics of lipid lowering drugs and diet network study. Clin Chem, 53, 1144-52.

CORELLA, D., TAI, E. S., SORLÍ, J. V., CHEW, S. K., COLTELL, O., SOTOS-PRIETO, M., GARCÍA-RIOS, A., ESTRUCH, R. & ORDOVAS, J. M. 2011. Association between the APOA2 promoter polymorphism and body weight in Mediterranean and Asian populations: replication of a gene-saturated fat interaction. Int J Obes (Lond), 35, 666-75.

CORNELIS, M. C., QI, L., KRAFT, P. & HU, F. B. 2009. TCF7L2, dietary carbohydrate, and risk of type 2 diabetes in US women. Am J Clin Nutr, 89, 1256-62.



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FALLAIZE, R., MACREADY, A. L., BUTLER, L. T., ELLIS, J. A. & LOVEGROVE, J. A. 2013. An insight into the public acceptance of nutrigenomic-based personalised nutrition. Nutr Res Rev, 26, 39-48.

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FERGUSON, J. F., PHILLIPS, C. M., MCMONAGLE, J., PÉREZ-MARTÍNEZ, P.,

SHAW, D. I., LOVEGROVE, J. A., HELAL, O., DEFOORT, C., GJELSTAD, I. M.,

DREVON, C. A., BLAAK, E. E., SARIS, W. H., LESZCZYŃSKA-GOŁABEK, I., KIEC-

WILK, B., RISÉRUS, U., KARLSTRÖM, B., LOPEZ-MIRANDA, J. & ROCHE, H. M.

2010. NOS3 gene polymorphisms are associated with risk markers of

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FERGUSON, L. R. & SCHLOTHAUER, R. C. 2012. The potential role of nutritional

genomics tools in validating high health foods for cancer control: broccoli as

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FRAYLING ,T.M et al 2007. A common variant in the FTO gene is associated

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GRAU, K., CAUCHI, S., HOLST, C., ASTRUP, A., MARTINEZ, J. A., SARIS, W. H., BLAAK, E. E., OPPERT, J. M., ARNER, P., RÖSSNER, S., MACDONALD, I. A., KLIMCAKOVA, E., LANGIN, D., PEDERSEN, O., FROGUEL, P. & SØRENSEN, T. I. 2010. TCF7L2 rs7903146-macronutrient interaction in obese individuals' responses to a 10-wk randomized hypoenergetic diet. Am J Clin Nutr, 91, 472-9.

GÖRMAN, U., MATHERS, J. C., GRIMALDI, K. A., AHLGREN, J. & NORDSTRÖM, K. 2013. Do we know enough? A scientific and ethical analysis of the basis for genetic-based personalized nutrition. Genes Nutr, 8, 373-81.

HESKETH, J. 2013. Personalised nutrition: how far has nutrigenomicsprogressed? Eur J Clin Nutr, 67, 430-5.

KAUWELL, G. P. 2008. Epigenetics: what it is and how it can affect dietetics practice. J Am Diet Assoc, 108, 1056-9.

KLERK, M., VERHOEF, P., CLARKE, R., BLOM, H. J., KOK, F. J., SCHOUTEN, E. G. & GROUP, M. S. C. 2002. MTHFR 677C-->T polymorphism and risk of coronary heart disease: a meta-analysis. JAMA, 288, 2023-31.



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LUAN

MARTÍNEZ, J. A., CORBALÁN, M. S., SÁNCHEZ-VILLEGAS, A., FORGA, L., MARTI, A. & MARTÍNEZ-GONZÁLEZ, M. A. 2003. Obesity risk is associated with carbohydrate intake in women carrying the Gln27Glu beta2-adrenoceptor polymorphism. J Nutr, 133, 2549-54.

MASUD, S., YE, S. & GROUP, S. 2003. Effect of the peroxisome proliferator activated receptor-gamma gene Pro12Ala variant on body mass index: a meta-analysis. J Med Genet,40, 773-80.

MASUO, K., KATSUYA, T., KAWAGUCHI, H., FU, Y., RAKUGI, H., OGIHARA, T. & TUCK, M. L. 2005. Rebound weight gain as associated with high plasma norepinephrine levels that are mediated through polymorphisms in the beta2-adrenoceptor. Am J Hypertens, 18, 1508-16.

Meisel

MEMISOGLU,A.,HU, F.B.,HANKINSON,S.E.,MANSON,J.E.,DE VIVO,I.,WILLETT,W.C.,HUNTER,D.J. 2003. Interaction between a peroxisome proliferator- activated receptor y gene polymorphism and dietary fat intake in relation to body mass. Human Molecular Genetics , 12, 22: 2923-2929



MOLERES, A., OCHOA, M. C., RENDO-URTEAGA, T., MARTÍNEZ-GONZÁLEZ, M.

A., AZCONA SAN JULIÁN, M. C., MARTÍNEZ, J. A., MARTI, A. & GENOI 2012.

Dietary fatty acid distribution modifies obesity risk linked to the rs9939609

polymorphism of the fat mass and obesity-associated gene in a Spanish case-

control study of children. Br J Nutr, 107, 533-8.

NIELSEN, D. E. & EL-SOHEMY, A. 2012. A randomized trial of genetic

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GONZÁLEZ, M., SALAS-SALVADÓ, J., COVAS, M. I., ARÓS, F., LAPETRA, J.,

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MUÑOZ, M. A., ROS, E., ORDOVÁS, J. M., ESTRUCH, R. & CORELLA, D. 2012.

Associations of the FTO rs9939609 and the MC4R rs17782313 polymorphisms

with type 2 diabetes are modulated by diet, being higher when adherence to

the Mediterranean diet pattern is low. Cardiovasc Diabetol, 11, 137.



REILLY, P. R. & DEBUSK, R. M. 2008. Ethical and legal issues in nutritional genomics. J Am Diet Assoc, 108, 36-40.

STOVER, P. J. & CAUDILL, M. A. 2008. Genetic and epigenetic contributions to human nutrition and health: managing genome-diet interactions. J Am Diet Assoc, 108, 1480-7.

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WENDEL, S., DELLAERT, B. G., RONTELTAP, A. & VAN TRIJP, H. C. 2013. Consumers' intention to use health recommendation systems to receive personalized nutrition advice. BMC Health Serv Res, 13, 126.

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Nutritional Genomics basics for nutrition …...MTHFR 677C>T ADRB3 Trp64Arg Rs 123456 Must know...

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