Personalized nutrition apps could provide valuable data to people trying to eat healthier, though more research must be done to show effectiveness.
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.”
Thanks to safety cautions from the COVID-19 pandemic, a strain of influenza has been completely eliminated.
The flu shot, explained
Influenza viruses type A and B are responsible for the majority of human illnesses and the flu season.
Centers for Disease Control
For more than a decade, flu shots have protected against two types of the influenza virus–type A and type B. While there are four different strains of influenza in existence (A, B, C, and D), only strains A, B, and C are capable of infecting humans, and only A and B cause pandemics. In other words, if you catch the flu during flu season, you’re most likely sick with flu type A or B.
Flu vaccines contain inactivated—or dead—influenza virus. These inactivated viruses can’t cause sickness in humans, but when administered as part of a vaccine, they teach a person’s immune system to recognize and kill those viruses when they’re encountered in the wild.
Each spring, a panel of experts gives a recommendation to the US Food and Drug Administration on which strains of each flu type to include in that year’s flu vaccine, depending on what surveillance data says is circulating and what they believe is likely to cause the most illness during the upcoming flu season. For the past decade, Americans have had access to vaccines that provide protection against two strains of influenza A and two lineages of influenza B, known as the Victoria lineage and the Yamagata lineage. But this year, the seasonal flu shot won’t include the Yamagata strain, because the Yamagata strain is no longer circulating among humans.
How Yamagata Disappeared
Flu surveillance data from the Global Initiative on Sharing All Influenza Data (GISAID) shows that the Yamagata lineage of flu type B has not been sequenced since April 2020.
Nature
Experts believe that the Yamagata lineage had already been in decline before the pandemic hit, likely because the strain was naturally less capable of infecting large numbers of people compared to the other strains. When the COVID-19 pandemic hit, the resulting safety precautions such as social distancing, isolating, hand-washing, and masking were enough to drive the virus into extinction completely.
Because the strain hasn’t been circulating since 2020, the FDA elected to remove the Yamagata strain from the seasonal flu vaccine. This will mark the first time since 2012 that the annual flu shot will be trivalent (three-component) rather than quadrivalent (four-component).
Should I still get the flu shot?
The flu shot will protect against fewer strains this year—but that doesn’t mean we should skip it. Influenza places a substantial health burden on the United States every year, responsible for hundreds of thousands of hospitalizations and tens of thousands of deaths. The flu shot has been shown to prevent millions of illnesses each year (more than six million during the 2022-2023 season). And while it’s still possible to catch the flu after getting the flu shot, studies show that people are far less likely to be hospitalized or die when they’re vaccinated.
Another unexpected benefit of dropping the Yamagata strain from the seasonal vaccine? This will possibly make production of the flu vaccine faster, and enable manufacturers to make more vaccines, helping countries who have a flu vaccine shortage and potentially saving millions more lives.
Founder Lewis Hornby and his grandmother Pat, sampling Jelly Drops—an edible gummy containing water and life-saving electrolytes.
When Lewis Hornby visited his grandmother at her nursing home afterward, he learned that dehydration especially affects people with dementia, as they often don’t feel thirst cues at all, or may not recognize how to use cups correctly. But while dementia patients often don’t remember to drink water, it seemed to Hornby that they had less problem remembering to eat, particularly candy.
Where people with dementia often forget to drink water, they're more likely to pick up a colorful snack, Hornby found. alzheimers.org.uk
Hornby wanted to create a solution for elderly people who struggled keeping their fluid intake up. He spent the next eighteen months researching and designing a solution and securing funding for his project. In 2019, Hornby won a sizable grant from the Alzheimer’s Society, a UK-based care and research charity for people with dementia and their caregivers. Together, through the charity’s Accelerator Program, they created a bite-sized, sugar-free, edible jelly drop that looked and tasted like candy. The candy, called Jelly Drops, contained 95% water and electrolytes—important minerals that are often lost during dehydration. The final product launched in 2020—and was an immediate success. The drops were able to provide extra hydration to the elderly, as well as help keep dementia patients safe, since dehydration commonly leads to confusion, hospitalization, and sometimes even death.
Not only did Jelly Drops quickly become a favorite snack among dementia patients in the UK, but they were able to provide an additional boost of hydration to hospital workers during the pandemic. In NHS coronavirus hospital wards, patients infected with the virus were regularly given Jelly Drops to keep their fluid levels normal—and staff members snacked on them as well, since long shifts and personal protective equipment (PPE) they were required to wear often left them feeling parched.
In April 2022, Jelly Drops launched in the United States. The company continues to donate 1% of its profits to help fund Alzheimer’s research.