Personalised Nutrition Based on Your DNA – Part 2 – Exploring the Evidence

Is it possible to create a completely personalised diet based on your genes?

This was the topic discussed in the first article of this series. The overall conclusion was yes, but only to a certain extent.

As technology and research advances, so too will the ability to refine and personalise diets.

But what about right now? This article will go further into the research linking certain gene variations and dietary recommendations.

Why Is Nutrigenomics Important?

Nutrition is a difficult and complex science to study.

Much of this can be attributed to the social and psychological aspects that accompany food choices and food preferences. Other lifestyle factors, such as exercise and alcohol consumption can also add to the confusion.

Nutrition research tries to identify if or how a specific nutrient causes a specific outcome. A cause and effect.

A major hurdle in this is individual genetic variation. Some people have an entirely different response to a nutrient due to their genetic make-up. A great example of this is coffee. Some people have a genetic variation which results in them processing caffeine differently, these people can be hypersensitive to the effects of caffeine. This is one of the reasons you see so much conflicting advice about coffee consumption.

Different individual responses to foods and nutrients, such as the above scenario, come down to genetic variation.
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Does Genetic Testing Have a Place in Nutrition Practice?

For nutritionists and dietitians, the knowledge gained from a genetic test could be instrumental to tailoring advice for clients. Especially for developing sustainable, and achievable lifestyle habits.

For example, if you identified a client as one of the 15% of the population with a variation at the FTO (Fat Mass and Obesity)gene. You would know they have genetic predisposition to increased appetite and decreased feelings of satiety. This could shape the kind of advice, skills and tools that would be used with that client. Certain approaches, such as intuitive eating, may perhaps be reconsidered.

Being able to pinpoint certain physiological responses to food is ultimately going to lead to better outcomes.

Setbacks when trying to achieve health goals can be demotivating and detrimental to self-confidence. Imagine the kind of results that could be produced with more precise recommendations.

The importance of genetics education among nutrition professionals is recognised, and Monash University recently funded a study to identify courses and training opportunities available within the field.(1)

Exploring the Science

A quick refresher on gene variations before reading the next section will help with understanding.

What is a polymorphism?

Polymorphisms are common variations in a gene. It is estimated that each individual has approximately 4 million genetic variations.

The type of genetic variations studied in most nutritional genomic research are SNPs (single nucleotide polymorphisms). This is when one nucleotide base is swapped for another. Read the first article for more explanation.

Each gene has thousands to hundreds of thousands of nucleotide base pairs. So, one gene has multiple SNP locations, there can be hundreds of SNPs within the same gene.

A specific location with a specific number is given for each SNP. For example in the FTO gene you might be looking at a SNP at the rs9939609 location or the rs1558902 location.

Changes in nucleotide bases are variations from the normal genotype. For example the normal (wild type) genotype might be AA and the variations AT or TT. These variations are also referred to as alleles.

Let’s take a look at some of the genes found in most nutrigenomic DNA tests. The specific locations are the ones used by myDNA. These locations are more relevant to nutrient metabolism and less to do with disease risk, such as cancer.

The ADIPOQ gene (Rs1501299)

Risk Allele = G

GG = High risk

GT = Moderate risk

TT = Normal risk

What does the ADIPOQ gene do?

The ADIPOQ gene contains instructions to make a hormone called adiponectin, it’s only expressed (turned on) in fat cells (adipocytes).

Adiponectin helps to break down fat cells and regulate blood glucose levels. Low adiponectin levels are seen in obesity, insulin resistance (decreased sensitivity to insulin) and type 2 diabetes.

A variation in the ADIPOQ gene is associated with lower adiponectin levels, and therefore is also associated with higher body fat levels and increased risk of type 2 diabetes.

One major difficulty when studying this gene is the difference between ethnicities. A variation at rs1501299 has been associated with obesity in Caucasians but not in Asians. However, variations at other locations in the ADIPOQ gene are associated with obesity in Asian populations. Given this information it would seem necessary to test for multiple locations and then give advice specific to ethnicity. However, current DNA tests do not account for ethnicity. (2-4)

The Evidence:

myDNA advise people with the risk allele GG or GT to

• Restrict calories by 300 kcal per day if overweight
• Avoid excess calorie consumption if normal weight, to avoid weight gain.
• Exercise regularly

The evidence myDNA provide for the ADIPOQ diet recommendations is based on a study of 294 overweight (BMI >23) Korean participants. They were put on a reduced calorie diet for 12 weeks. The diet was 300/kcal less than their overall energy requirements. Those with two of the risk alleles (GG) saw significant increases in adiponectin levels and decreased insulin resistance; whereas those with at least one copy of the low risk T allele did not. This study was of course done in a Korean population which means these results may not be replicated in other ethnicities. (5)

These results were similar to another study of 248 obese Caucasian participants. Those with two copies of the risk allele (GG) at rs1501299 had increased adiponectin levels and increased insulin sensitivity after weight loss. The type of diet (moderate carbohydrate vs low fat) did not appear to have any affect. These results were not seen in the other genotypes, again this study had no control group and a small number of participants. (6)

Supporting evidence for the specific recommendation to reduce calories by 300/kcal is minimal. Having said that, the overall advice for moderate calorie reduction is still solid. Other studies have shown weight reduction and exercise can help normalise adiponectin levels in overweight and obese participants. However, these studies were not specific to individual genotypes. (7)

The Verdict:

It seems the advice myDNA give is practical even if essentially intuitive.

Overall, advice to reduce calorie consumption and exercise more if overweight; and for normal weight people with the risk variant to watch energy intake, is actionable and has supporting evidence.

However, the very specific advice to reduce calorie consumption by 300 kcal seems a little misplaced.

The PPARG gene (rs1801282)

Risk allele = C

High risk = CC

Normal Risk = CG and GG

What does the ADIPOQ gene do?

The PPARG gene is an interesting one because a variation in this gene could actually be beneficial.

The PPARG gene determines if your body is good at storing fat when you consume excess energy. This is why it is otherwise known as the ‘thrifty gene’. It’s thrifty because it saves excess energy as body fat for later time, when there may be no food available. This would have been beneficial back in the hunter-gatherer days. Now we live in an age of excess energy and this fat storage is not so necessary for survival.

People with the normal CC gene are sensitive to dietary fat, may have a higher BMI if excess energy is consumed and an elevated risk of type 2 diabetes.(8, 9)

A variation at this gene means your body is not good at storing fat and will likely have a lower BMI and a reduced risk of diabetes. However, these protective effects seem to dissipate with overweight or obesity. This makes studying the effects of different dietary patterns on this gene quite complex.

The Evidence:

myDNA recommend the following for people with the two normal CC alleles:

• Limit total dietary fat to less than 25%
• Increase polyunsaturated fats in the diet, from sources such as avocado, nuts and oily fish
• Keep saturated fat intake to less than 10% of total fat intake

Many studies looking at various diets and the effect on weight loss in relation to a variation at the PPARG gene are done in obese, pre-diabetic or insulin resistant populations. The results of these studies therefore may not be relevant to people with lower body fat or normal insulin tolerance.

Weight loss interventions (diets) seem to be more effective in people who have at least one copy of the G allele. For carriers of the CC alleles the evidence is conflicting. Currently there is minimal evidence to support specific dietary recommendations for people with the normal CC allele.

Some evidence does suggest a diet higher in polyunsaturated fat and lower in saturated fat may help keep body fat levels lower in the CC genotype. Also, high total fat intake appears to be linked to increased body fat in people with the CC genotype compared to those with at least one G allele.

In a large observational study of 2141 woman, a high fat diet increased the risk of a higher body weight and obesity in women with the CC genotype. This relationship was not seen in women with at least one C allele. The researchers also concluded that a higher polyunsaturated to saturated fat ratio was associated with a lower BMI in the CC genotype, again this was not seen with the G variant. High saturated fat intake was associated with a higher BMI across all genotypes.(10)

This is particularly interesting given the recent trend towards high-fat low-carbohydrate diets. People with the CG or GG variant may do well on this type of diet whereas people with the normal CC, which is the majority of the population, would probably not.

The Verdict:

Overall, there could be more evidence to support the recommendation to limit fat in the diet. However, it is still reasonable advice that is relatively easy for people to implement.

In Conclusion

The interaction between diet and genes is incredibly complex, which makes evaluating the evidence difficult. Another concern is the difference in gene association among various ethnicities. A gene variation in Asian populations for example may not produce the same outcome as they do in Caucasian populations.

For the most part there is evidence to support certain dietary advice for people with specific gene variations.

The benefits of using nutritional genomic tests in nutrition practice seem to outweigh any potential downsides. One barrier may be the high cost of genetic testing. However, there are some affordable tests currently available in Australia such as myDNA.

References

1. Collins J, Adamski MM, Twohig C, Murgia C. Opportunities for Training for Nutritional Professionals in Nutritional Genomics: What Is out There? Nutrition & Dietetics. 2017.
2. Lu J-f, Zhou Y, Huang G-h, Jiang H-x, Hu B-l, Qin S-y. Association of Adipoq Polymorphisms with Obesity Risk: A Meta-Analysis. Human Immunology. 2014;75:1062-8.
3. Tu Y, Yu Q, Yang P, Lai Q, Zhang S, Wang D, et al. Assessment of Type 2 Diabetes Risk Conferred by Snps Rs2241766 and Rs1501299 in the Adipoq Gene, a Case/Control Study Combined with Meta-Analyses. Molecular and Cellular Endocrinology. 2014;396(1-2):1-9.
4. Wu J, Liu Z, Meng K, Zhang L. Association of Adiponectin Gene (Adipoq) Rs2241766 Polymorphism with Obesity in Adults: A Meta-Analysis. PLoS One. 2014;9(4):e95270.
5. Shin M-J, Jang Y, Koh SJ, Chae JS, Kim OY, Lee JE, et al. The Association of Snp276g> T at Adiponectin Gene with Circulating Adiponectin and Insulin Resistance in Response to Mild Weight Loss. International journal of obesity. 2006;30(12):1702.
6. de Luis DA, Izaola O, Primo D, Aller R, Ortola A, Gómez E, et al. The Association of Snp276g> T at Adiponectin Gene with Insulin Resistance and Circulating Adiponectin in Response to Two Different Hypocaloric Diets. Diabetes research and clinical practice. 2018.
7. Salehi-Abargouei A, Izadi V, Azadbakht L. The Effect of Low Calorie Diet on Adiponectin Concentration: A Systematic Review and Meta-Analysis. Hormone and Metabolic Research. 2015;47(08):549-55.
8. Gouda HN, Sagoo GS, Harding A-H, Yates J, Sandhu MS, Higgins JP. The Association between the Peroxisome Proliferator-Activated Receptor-Γ2 (Pparg2) Pro12ala Gene Variant and Type 2 Diabetes Mellitus: A Huge Review and Meta-Analysis. American journal of epidemiology. 2010;171(6):645-55.
9. Yao Y-s, Li J, Jin Y-l, Chen Y, He L-p. Association between Ppar-Γ2 Pro12ala Polymorphism and Obesity: A Meta-Analysis. Molecular biology reports. 2015;42(6):1029-38.
10. Memisoglu A, Hu FB, Hankinson SE, Manson JE, De Vivo I, Willett WC, et al. Interaction between a Peroxisome Proliferator-Activated Receptor Γ Gene Polymorphism and Dietary Fat Intake in Relation to Body Mass. Human molecular genetics. 2003;12(22):2923-9.