AI and you: Is the promise of personalized nutrition apps worth the hype?
As a type 2 diabetic, Michael Snyder has long been interested in how blood sugar levels vary from one person to another in response to the same food, and whether a more personalized approach to nutrition could help tackle the rapidly cascading levels of diabetes and obesity in much of the western world.
Eight years ago, Snyder, who directs the Center for Genomics and Personalized Medicine at Stanford University, decided to put his theories to the test. In the 2000s continuous glucose monitoring, or CGM, had begun to revolutionize the lives of diabetics, both type 1 and type 2. Using spherical sensors which sit on the upper arm or abdomen – with tiny wires that pierce the skin – the technology allowed patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
It gave Snyder an idea for his research at Stanford. Applying the same technology to a group of apparently healthy people, and looking for ‘spikes’ or sudden surges in blood sugar known as hyperglycemia, could provide a means of observing how their bodies reacted to an array of foods.
“We discovered that different foods spike people differently,” he says. “Some people spike to pasta, others to bread, others to bananas, and so on. It’s very personalized and our feeling was that building programs around these devices could be extremely powerful for better managing people’s glucose.”
Unbeknown to Snyder at the time, thousands of miles away, a group of Israeli scientists at the Weizmann Institute of Science were doing exactly the same experiments. In 2015, they published a landmark paper which used CGM to track the blood sugar levels of 800 people over several days, showing that the biological response to identical foods can vary wildly. Like Snyder, they theorized that giving people a greater understanding of their own glucose responses, so they spend more time in the normal range, may reduce the prevalence of type 2 diabetes.
The commercial potential of such apps is clear, but the underlying science continues to generate intriguing findings.
“At the moment 33 percent of the U.S. population is pre-diabetic, and 70 percent of those pre-diabetics will become diabetic,” says Snyder. “Those numbers are going up, so it’s pretty clear we need to do something about it.”
Fast forward to 2022,and both teams have converted their ideas into subscription-based dietary apps which use artificial intelligence to offer data-informed nutritional and lifestyle recommendations. Snyder’s spinoff, January AI, combines CGM information with heart rate, sleep, and activity data to advise on foods to avoid and the best times to exercise. DayTwo–a start-up which utilizes the findings of Weizmann Institute of Science–obtains microbiome information by sequencing stool samples, and combines this with blood glucose data to rate ‘good’ and ‘bad’ foods for a particular person.
“CGMs can be used to devise personalized diets,” says Eran Elinav, an immunology professor and microbiota researcher at the Weizmann Institute of Science in addition to serving as a scientific consultant for DayTwo. “However, this process can be cumbersome. Therefore, in our lab we created an algorithm, based on data acquired from a big cohort of people, which can accurately predict post-meal glucose responses on a personal basis.”
The commercial potential of such apps is clear. DayTwo, who market their product to corporate employers and health insurers rather than individual consumers, recently raised $37 million in funding. But the underlying science continues to generate intriguing findings.
Last year, Elinav and colleagues published a study on 225 individuals with pre-diabetes which found that they achieved better blood sugar control when they followed a personalized diet based on DayTwo’s recommendations, compared to a Mediterranean diet. The journal Cell just released a new paper from Snyder’s group which shows that different types of fibre benefit people in different ways.
“The idea is you hear different fibres are good for you,” says Snyder. “But if you look at fibres they’re all over the map—it’s like saying all animals are the same. The responses are very individual. For a lot of people [a type of fibre called] arabinoxylan clearly reduced cholesterol while the fibre inulin had no effect. But in some people, it was the complete opposite.”
Eight years ago, Stanford's Michael Snyder began studying how continuous glucose monitors could be used by patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
The Snyder Lab, Stanford Medicine
Because of studies like these, interest in precision nutrition approaches has exploded in recent years. In January, the National Institutes of Health announced that they are spending $170 million on a five year, multi-center initiative which aims to develop algorithms based on a whole range of data sources from blood sugar to sleep, exercise, stress, microbiome and even genomic information which can help predict which diets are most suitable for a particular individual.
“There's so many different factors which influence what you put into your mouth but also what happens to different types of nutrients and how that ultimately affects your health, which means you can’t have a one-size-fits-all set of nutritional guidelines for everyone,” says Bruce Y. Lee, professor of health policy and management at the City University of New York Graduate School of Public Health.
With the falling costs of genomic sequencing, other precision nutrition clinical trials are choosing to look at whether our genomes alone can yield key information about what our diets should look like, an emerging field of research known as nutrigenomics.
The ASPIRE-DNA clinical trial at Imperial College London is aiming to see whether particular genetic variants can be used to classify individuals into two groups, those who are more glucose sensitive to fat and those who are more sensitive to carbohydrates. By following a tailored diet based on these sensitivities, the trial aims to see whether it can prevent people with pre-diabetes from developing the disease.
But while much hope is riding on these trials, even precision nutrition advocates caution that the field remains in the very earliest of stages. Lars-Oliver Klotz, professor of nutrigenomics at Friedrich-Schiller-University in Jena, Germany, says that while the overall goal is to identify means of avoiding nutrition-related diseases, genomic data alone is unlikely to be sufficient to prevent obesity and type 2 diabetes.
“Genome data is rather simple to acquire these days as sequencing techniques have dramatically advanced in recent years,” he says. “However, the predictive value of just genome sequencing is too low in the case of obesity and prediabetes.”
Others say that while genomic data can yield useful information in terms of how different people metabolize different types of fat and specific nutrients such as B vitamins, there is a need for more research before it can be utilized in an algorithm for making dietary recommendations.
“I think it’s a little early,” says Eileen Gibney, a professor at University College Dublin. “We’ve identified a limited number of gene-nutrient interactions so far, but we need more randomized control trials of people with different genetic profiles on the same diet, to see whether they respond differently, and if that can be explained by their genetic differences.”
Some start-ups have already come unstuck for promising too much, or pushing recommendations which are not based on scientifically rigorous trials. The world of precision nutrition apps was dubbed a ‘Wild West’ by some commentators after the founders of uBiome – a start-up which offered nutritional recommendations based on information obtained from sequencing stool samples –were charged with fraud last year. The weight-loss app Noom, which was valued at $3.7 billion in May 2021, has been criticized on Twitter by a number of users who claimed that its recommendations have led to them developed eating disorders.
With precision nutrition apps marketing their technology at healthy individuals, question marks have also been raised about the value which can be gained through non-diabetics monitoring their blood sugar through CGM. While some small studies have found that wearing a CGM can make overweight or obese individuals more motivated to exercise, there is still a lack of conclusive evidence showing that this translates to improved health.
However, independent researchers remain intrigued by the technology, and say that the wealth of data generated through such apps could be used to help further stratify the different types of people who become at risk of developing type 2 diabetes.
“CGM not only enables a longer sampling time for capturing glucose levels, but will also capture lifestyle factors,” says Robert Wagner, a diabetes researcher at University Hospital Düsseldorf. “It is probable that it can be used to identify many clusters of prediabetic metabolism and predict the risk of diabetes and its complications, but maybe also specific cardiometabolic risk constellations. However, we still don’t know which forms of diabetes can be prevented by such approaches and how feasible and long-lasting such self-feedback dietary modifications are.”
Snyder himself has now been wearing a CGM for eight years, and he credits the insights it provides with helping him to manage his own diabetes. “My CGM still gives me novel insights into what foods and behaviors affect my glucose levels,” he says.
He is now looking to run clinical trials with his group at Stanford to see whether following a precision nutrition approach based on CGM and microbiome data, combined with other health information, can be used to reverse signs of pre-diabetes. If it proves successful, January AI may look to incorporate microbiome data in future.
“Ultimately, what I want to do is be able take people’s poop samples, maybe a blood draw, and say, ‘Alright, based on these parameters, this is what I think is going to spike you,’ and then have a CGM to test that out,” he says. “Getting very predictive about this, so right from the get go, you can have people better manage their health and then use the glucose monitor to help follow that.”
In May 2022, Californian biotech Ultima Genomics announced that its UG 100 platform was capable of sequencing an entire human genome for just $100, a landmark moment in the history of the field. The announcement was particularly remarkable because few had previously heard of the company, a relative unknown in an industry long dominated by global giant Illumina which controls about 80 percent of the world’s sequencing market.
Ultima’s secret was to completely revamp many technical aspects of the way Illumina have traditionally deciphered DNA. The process usually involves first splitting the double helix DNA structure into single strands, then breaking these strands into short fragments which are laid out on a glass surface called a flow cell. When this flow cell is loaded into the sequencing machine, color-coded tags are attached to each individual base letter. A laser scans the bases individually while a camera simultaneously records the color associated with them, a process which is repeated until every single fragment has been sequenced.
Instead, Ultima has found a series of shortcuts to slash the cost and boost efficiency. “Ultima Genomics has developed a fundamentally new sequencing architecture designed to scale beyond conventional approaches,” says Josh Lauer, Ultima’s chief commercial officer.
This ‘new architecture’ is a series of subtle but highly impactful tweaks to the sequencing process ranging from replacing the costly flow cell with a silicon wafer which is both cheaper and allows more DNA to be read at once, to utilizing machine learning to convert optical data into usable information.
To put $100 genome in perspective, back in 2012 the cost of sequencing a single genome was around $10,000, a price tag which dropped to $1,000 a few years later. Before Ultima’s announcement, the cost of sequencing an individual genome was around $600.
Several studies have found that nearly 12 percent of healthy people who have their genome sequenced, then discover they have a variant pointing to a heightened risk of developing a disease that can be monitored, treated or prevented.
While Ultima’s new machine is not widely available yet, Illumina’s response has been rapid. Last month the company unveiled the NovaSeq X series, which it describes as its fastest most cost-efficient sequencing platform yet, capable of sequencing genomes at $200, with further price cuts likely to follow.
But what will the rapidly tumbling cost of sequencing actually mean for medicine? “Well to start with, obviously it’s going to mean more people getting their genome sequenced,” says Michael Snyder, professor of genetics at Stanford University. “It'll be a lot more accessible to people.”
At the moment sequencing is mainly limited to certain cancer patients where it is used to inform treatment options, and individuals with undiagnosed illnesses. In the past, initiatives such as SeqFirst have attempted further widen access to genome sequencing based on growing amounts of research illustrating the potential benefits of the technology in healthcare. Several studies have found that nearly 12 percent of healthy people who have their genome sequenced, then discover they have a variant pointing to a heightened risk of developing a disease that can be monitored, treated or prevented.
“While whole genome sequencing is not yet widely used in the U.S., it has started to come into pediatric critical care settings such as newborn intensive care units,” says Professor Michael Bamshad, who heads the genetic medicine division in the University of Washington’s pediatrics department. “It is also being used more often in outpatient clinical genetics services, particularly when conventional testing fails to identify explanatory variants.”
But the cost of sequencing itself is only one part of the price tag. The subsequent clinical interpretation and genetic counselling services often come to several thousand dollars, a cost which insurers are not always willing to pay.
As a result, while Bamshad and others hope that the arrival of the $100 genome will create new opportunities to use genetic testing in innovative ways, the most immediate benefits are likely to come in the realm of research.
Bigger Data
There are numerous ways in which cheaper sequencing is likely to advance scientific research, for example the ability to collect data on much larger patient groups. This will be a major boon to scientists working on complex heterogeneous diseases such as schizophrenia or depression where there are many genes involved which all exert subtle effects, as well as substantial variance across the patient population. Bigger studies could help scientists identify subgroups of patients where the disease appears to be driven by similar gene variants, who can then be more precisely targeted with specific drugs.
If insurers can figure out the economics, Snyder even foresees a future where at a certain age, all of us can qualify for annual sequencing of our blood cells to search for early signs of cancer or the potential onset of other diseases like type 2 diabetes.
David Curtis, a genetics professor at University College London, says that scientists studying these illnesses have previously been forced to rely on genome-wide association studies which are limited because they only identify common gene variants. “We might see a significant increase in the number of large association studies using sequence data,” he says. “It would be far preferable to use this because it provides information about rare, potentially functional variants.”
Cheaper sequencing will also aid researchers working on diseases which have traditionally been underfunded. Bamshad cites cystic fibrosis, a condition which affects around 40,000 children and adults in the U.S., as one particularly pertinent example.
“Funds for gene discovery for rare diseases are very limited,” he says. “We’re one of three sites that did whole genome sequencing on 5,500 people with cystic fibrosis, but our statistical power is limited. A $100 genome would make it much more feasible to sequence everyone in the U.S. with cystic fibrosis and make it more likely that we discover novel risk factors and pathways influencing clinical outcomes.”
For progressive diseases that are more common like cancer and type 2 diabetes, as well as neurodegenerative conditions like multiple sclerosis and ALS, geneticists will be able to go even further and afford to sequence individual tumor cells or neurons at different time points. This will enable them to analyze how individual DNA modifications like methylation, change as the disease develops.
In the case of cancer, this could help scientists understand how tumors evolve to evade treatments. Within in a clinical setting, the ability to sequence not just one, but many different cells across a patient’s tumor could point to the combination of treatments which offer the best chance of eradicating the entire cancer.
“What happens at the moment with a solid tumor is you treat with one drug, and maybe 80 percent of that tumor is susceptible to that drug,” says Neil Ward, vice president and general manager in the EMEA region for genomics company PacBio. “But the other 20 percent of the tumor has already got mutations that make it resistant, which is probably why a lot of modern therapies extend life for sadly only a matter of months rather than curing, because they treat a big percentage of the tumor, but not the whole thing. So going forwards, I think that we will see genomics play a huge role in cancer treatments, through using multiple modalities to treat someone's cancer.”
If insurers can figure out the economics, Snyder even foresees a future where at a certain age, all of us can qualify for annual sequencing of our blood cells to search for early signs of cancer or the potential onset of other diseases like type 2 diabetes.
“There are companies already working on looking for cancer signatures in methylated DNA,” he says. “If it was determined that you had early stage cancer, pre-symptomatically, that could then be validated with targeted MRI, followed by surgery or chemotherapy. It makes a big difference catching cancer early. If there were signs of type 2 diabetes, you could start taking steps to mitigate your glucose rise, and possibly prevent it or at least delay the onset.”
This would already revolutionize the way we seek to prevent a whole range of illnesses, but others feel that the $100 genome could also usher in even more powerful and controversial preventative medicine schemes.
Newborn screening
In the eyes of Kári Stefánsson, the Icelandic neurologist who been a visionary for so many advances in the field of human genetics over the last 25 years, the falling cost of sequencing means it will be feasible to sequence the genomes of every baby born.
“We have recently done an analysis of genomes in Iceland and the UK Biobank, and in 4 percent of people you find mutations that lead to serious disease, that can be prevented or dealt with,” says Stefansson, CEO of deCODE genetics, a subsidiary of the pharmaceutical company Amgen. “This could transform our healthcare systems.”
As well as identifying newborns with rare diseases, this kind of genomic information could be used to compute a person’s risk score for developing chronic illnesses later in life. If for example, they have a higher than average risk of colon or breast cancer, they could be pre-emptively scheduled for annual colonoscopies or mammograms as soon as they hit adulthood.
To a limited extent, this is already happening. In the UK, Genomics England has launched the Newborn Genomes Programme, which plans to undertake whole-genome sequencing of up to 200,000 newborn babies, with the aim of enabling the early identification of rare genetic diseases.
"I have not had my own genome sequenced and I would not have wanted my parents to have agreed to this," Curtis says. "I don’t see that sequencing children for the sake of some vague, ill-defined benefits could ever be justifiable.”
However, some scientists feel that it is tricky to justify sequencing the genomes of apparently healthy babies, given the data privacy issues involved. They point out that we still know too little about the links which can be drawn between genetic information at birth, and risk of chronic illness later in life.
“I think there are very difficult ethical issues involved in sequencing children if there are no clear and immediate clinical benefits,” says Curtis. “They cannot consent to this process. I have not had my own genome sequenced and I would not have wanted my parents to have agreed to this. I don’t see that sequencing children for the sake of some vague, ill-defined benefits could ever be justifiable.”
Curtis points out that there are many inherent risks about this data being available. It may fall into the hands of insurance companies, and it could even be used by governments for surveillance purposes.
“Genetic sequence data is very useful indeed for forensic purposes. Its full potential has yet to be realized but identifying rare variants could provide a quick and easy way to find relatives of a perpetrator,” he says. “If large numbers of people had been sequenced in a healthcare system then it could be difficult for a future government to resist the temptation to use this as a resource to investigate serious crimes.”
While sequencing becoming more widely available will present difficult ethical and moral challenges, it will offer many benefits for society as a whole. Cheaper sequencing will help boost the diversity of genomic datasets which have traditionally been skewed towards individuals of white, European descent, meaning that much of the actionable medical information which has come out of these studies is not relevant to people of other ethnicities.
Ward predicts that in the coming years, the growing amount of genetic information will ultimately change the outcomes for many with rare, previously incurable illnesses.
“If you're the parent of a child that has a susceptible or a suspected rare genetic disease, their genome will get sequenced, and while sadly that doesn’t always lead to treatments, it’s building up a knowledge base so companies can spring up and target that niche of a disease,” he says. “As a result there’s a whole tidal wave of new therapies that are going to come to market over the next five years, as the genetic tools we have, mature and evolve.”
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here is the promising research covered in this week's Friday Five:
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- How to make cities of the future less noisy
- An old diabetes drug could have a new purpose: treating an irregular heartbeat
- A new reason for mysterious stillbirths
- Making old mice younger with EVs
- No pain - or mucus - no gain
And an honorable mention this week: How treatments for depression can change the structure of the brain