Written by Lewis Wallis Edited by Swathi Kumar & Natasha Barrow
The word 'personalised' in the world of nutrition may have started out as a trendy idea, but it has now started to become a serious reality. Companies have been jumping on board to offer personalised dietary advice, recommendations and even products based on individual characteristics.
Current dietary advice, including government recommendations and guidelines, is generally non-personalised and targeted for whole populations. Despite this, every person on the planet has features which make them unique. This includes distinct genetic information (genome) and individual gut bacteria profiles (microbiome), alongside food preferences and tolerances, all of which can be shaped by the environment we live in. Information collected about these factors can be used to develop targeted dietary advice and can aid the implementation of lasting behavioural changes – these concepts are known as ‘personalised nutrition’. A recent systematic review of available evidence concluded that giving nutrition advice, which is personalised, can have a greater effect than generalised recommendations[1]. However, there is limited evidence to confirm that providing information based on genetics is effective at improving diets.
Personalised nutrition can also be effective in combination with technology. An app developed at University of Reading giving individuals personalised nutrition feedback, based on their current dietary habits, managed to improve the monitored 'healthy diet score' by 6% compared to those receiving general advice [2].
Every cell in the body contains your unique DNA sequence which encodes genetic information (genes). This sequence is like a code which holds all the instructions for protein production within our body. Each protein carries out specific functions within cells to help maintain important processes that are required for survival. Genetic variation exists between individuals and the most common type are known as Single Nucleotide Polymorphisms (SNPs, pronounced "snips"). In essence, a SNP is a switch in the DNA sequence where one nucleotide is replaced for another. Some switches can be linked directly to particular diseases and even be used to predict the risk of developing the disease.
Some harmful variants can be inherited and subsequently increase the risk of diseases such as some cancers. For example, mutations in BRCA1 and BRCA2 genes, which are utilised for DNA repair, can increase the risk of breast and ovarian cancer [3], with genetic testing offered by the NHS4. Another important component of tumour-supressing mechanisms is the p53 protein and mutation in this gene (Li-Fraumeni syndrome) also increases the risk of several cancers.
Genetic information about variants can be analysed statistically to provide a 'polygenic risk score', which is used to estimate the risk of developing a condition. However, the score is an estimation based on current knowledge of specific genes involved and future research may give a wider understanding into even more genes. Polygenic risk scores give no indication into how, if or when the disease will occur. They only show correlations and taking other factors, like age, into account would alter the risk level proposed. Currently, there are no guidelines for use of such scores by healthcare providers and limitations exist with accuracy and the need to develop further knowledge of the genes involved.
In recent years, direct-to-consumer test kits have been sold for around £100 by companies such as 23andMe, in a bid to "understand" and develop reports on your genetic information, proposing to give insights into the risk of developing conditions like Type 2 Diabetes or Coeliac Disease. These tests generally aim to identify specific SNPs although some do sequence the entire genome. To find out more, have a listen to the podcast by The British Medical Journal (BMJ).
https://www.genome.gov/dna-day/15-ways/direct-to-consumer-genomic-testing
Advice based on genetics can be developed by identifying single genes which are affected by particular dietary factors or by evaluating genetic risk scores which combine multiple SNPs of interest. Some companies may promise or imply they can give information about the future health of individuals using polygenic risk scores but interpreting how SNPs alter the predisposition/progression of some diseases can be difficult and may not give the most accurate picture about your future health. It is worth considering how the resulting information could affect your lifestyle and mental health as receiving a 'negative' result may unnecessarily elevate levels of concern. Highlighting an increased risk of disease from genetic testing does not confirm that it will definitely develop in the individual and false positives/negatives are possible.
Furthermore, products have made overstated claims in the past, for example recently the Advertising Standards Authority (ASA) adjudication blocked a social media ad for making misleading claims about the potential of their testing kit to ‘unlock the secret to your ideal diet’ [5]. Companies selling DNA testing kits should ensure the information is clear, providing details on any limitations and avoid advertising in a way which misleads consumers into thinking that knowing their genetic insights will lead to sustained dietary/lifestyle behaviour change.
Overall, genetic information is not the ultimate predictor of disease. We live in a world where we are exposed to many environmental factors and although your DNA may predispose you to a certain condition, external factors e.g. diet, smoking, obesity, alcohol intake and age can alter the risk of disease development.
The gut microbiome is the complex collection of bacteria, fungi and other microbes that live in our small and large intestines. I had the chance to have my gut microbiome sequenced as part of a citizen science research project by The Microsetta Initiative. After providing a stool sample and completing questionnaires relating to dietary habits and environmental exposures, I received a report detailing the diversity of my gut microbiome and how it compared to others.
Example of information received from The Microsetta Initiative:
Individuals can respond completely differently to the same foods and elicit a different physiological response after a meal. After finding such high variability in an 800-participant study, the authors successfully developed an algorithm based on personal data from blood tests, food diaries and the microbiome to design personalised dietary advice to reduce blood sugar responses [6].
Even identical twins, who share the same genes, can have varying lifestyle factors which may shift the microbiome profile and lead to a differing response to the same meal. Again, using data from this study, a machine learning model was developed, which could predict how the individual's fatty acid and sugar levels would respond based on meal composition and personal factors including genetics and the microbiome [7].
The PREDICT program is a series of clinical trials which aim to describe how and why individuals respond differently to meals and identify factors that can affect this response. After collecting baseline data about individual responses, the PREDICT-1 study led to development of an algorithm which could predict how different individuals would respond [8]. In this study, genetics were not a predominant factor affecting the response. Therefore, using only individual DNA data would be unlikely to be enough to understand how an individual responds to foods. Other factors including exercise, sleep and time of meal are important components of the response. Incorporating data on the diversity of each individual's gut microbiome strengthened the ability of the algorithm to predict the response, emphasising how microbiome analysis can be a useful tool to further develop personalised nutrition advice. The PREDICT-2 study was carried out by participants entirely remotely, which led to the development of at-home testing products now used by the ZOE project described further below.
ZOE is a personalised nutrition company that has invited 180,000 to a waiting list for its upcoming product, aiming to bring personalised nutrition to the mass market and give foods personalised scores based on consumer information. The company differs to others as it combines a variety of tests which collect your blood sugar, blood fat and microbiome data without testing for genetic information. From this they will provide a detailed report on the results as well as a weekly personalised plan, with scores for individual foods and meal suggestions which aim to improve your gut health and reduce dietary inflammation.
The company DayTwo also commercialised an algorithm developed by research, offering customers the opportunity to have their microbiome data, blood tests and personal information analysed to provide personalised recommendations for foods which will reduce blood sugar responses.
Another interesting example comes from the NHS which plans to use a health app to deliver personalised diet and exercise advice for the run-up to operations and the recovery phase. Keeping in touch with a coach via a 20-minute call each week will be used to monitor progress, with the overall cost per patient to the NHS at £120. In doing so, they aim to increase recovery times and reduce the number of post-surgery complications.
With the aim to 'optimise your health', BIONIQ offers personalised supplements after testing over 30 health parameters relating to your vitamin and mineral status. From £39 per month, the company delivers personalised supplements and gives health advice via its app.
Similar to BIONIQ, food and beverage company Nestlé has trialled a personalised nutrition approach in Japan, where around 100,000 users send images of their food via an app. Nestlé uses these results and data from DNA and blood tests before creating personalised recommendations and supplements, which when received can be used to make teas, smoothies and other fortified snacks.
Dietary advice that is personalised for individuals can be effective when it comes to implementing lasting behaviour change and the personalised nutrition industry is expanding year on year. Further research will continue to contribute to our understanding of the factors involved and subsequently aid the development of algorithms to predict responses to foods. Development in technologies like wearable devices may also further integrate into upcoming personalised nutrition solutions and lead to a future where we continuously monitor our data to gain a holistic view of the personal factors that influence our unique response to food.
References
1https://pubmed.ncbi.nlm.nih.gov/33313795/
2https://www.reading.ac.uk/news/2022/Research-News/Nutrition-advice-app
6https://www.cell.com/fulltext/S0092-8674(15)01481-6
7https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265154/
8https://www.nature.com/articles/s41591-020-0934-0
For extra information:
BMJ Podcast: https://www.bmj.com/content/367/bmj.l5688
Polygenic Risk Scores: https://www.genome.gov/Health/Genomics-and-Medicine/Polygenic-risk-scores
NHS Personalised Health App Information: https://www.dailymail.co.uk/health/article-10840537/NHS-patients-receive-120-private-health-app-fit-surgery.html
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