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.”
Leading XPRIZE Healthspan and Beating Negativity with Dr. Peter Diamandis
A new competition by the XPRIZE Foundation is offering $101 million to researchers who discover therapies that give a boost to people aged 65-80 so their bodies perform more like when they were middle-aged.
For today’s podcast episode, I talked with Dr. Peter Diamandis, XPRIZE’s founder and executive chairman. Under Peter’s leadership, XPRIZE has launched 27 previous competitions with over $300 million in prize purses. The latest contest aims to enhance healthspan, or the period of life when older people can play with their grandkids without any restriction, disability or disease. Such breakthroughs could help prevent chronic diseases that are closely linked to aging. These illnesses are costly to manage and threaten to overwhelm the healthcare system, as the number of Americans over age 65 is rising fast.
In this competition, called XPRIZE Healthspan, multiple awards are available, depending on what’s achieved, with support from the nonprofit Hevolution Foundation and Chip Wilson, the founder of Lululemon and nonprofit SOLVE FSHD. The biggest prize, $81 million, is for improvements in cognition, muscle and immunity by 20 years. An improvement of 15 years will net $71 million, and 10 years will net $61 million.
In our conversation for this episode, Peter talks about his plans for XPRIZE Healthspan and why exponential technologies make the current era - even with all of its challenges - the most exciting time in human history. We discuss the best mental outlook that supports a person in becoming truly innovative, as well as the downsides of too much risk aversion. We talk about how to overcome the negativity bias in ourselves and in mainstream media, how Peter has shifted his own mindset to become more positive over the years, how to inspire a culture of innovation, Peter’s personal recommendations for lifestyle strategies to live longer and healthier, the innovations we can expect in various fields by 2030, the future of education and the importance of democratizing tech and innovation.
In addition to Peter’s pioneering leadership of XPRIZE, he is also the Executive Founder of Singularity University. In 2014, he was named by Fortune as one of the “World’s 50 Greatest Leaders.” As an entrepreneur, he’s started over 25 companies in the areas of health-tech, space, venture capital and education. He’s Co-founder and Vice-Chairman of two public companies, Celularity and Vaxxinity, plus being Co-founder & Chairman of Fountain Life, a fully-integrated platform delivering predictive, preventative, personalized and data-driven health. He also serves as Co-founder of BOLD Capital Partners, a venture fund with a half-billion dollars under management being invested in exponential technologies and longevity companies. Peter is a New York Times Bestselling author of four books, noted during our conversation and in the show notes of this episode. He has degrees in molecular genetics and aerospace engineering from MIT and holds an M.D. from Harvard Medical School.
Show links
- Peter Diamandis bio
- New XPRIZE Healthspan
- Peter Diamandis books
- 27 XPRIZE competitions and counting
- Life Force by Peter Diamandis and Tony Robbins
- Peter Diamandis Twitter
- Longevity Insider newsletter – AI identifies the news
- Peter Diamandis Longevity Handbook
- Hevolution funding for longevity
XPRIZE Founder Peter Diamandis speaks with Mehmoud Khan, CEO of Hevolution Foundation, at the launch of XPRIZE Healthspan.
Hevolution Foundation
From infections with no symptoms to why men are more likely to be hospitalized in the ICU and die of COVID-19, new research shows that your genes play a significant role
Early in the pandemic, genetic research focused on the virus because it was readily available. Plus, the virus contains only 30,000 bases in a dozen functional genes, so it's relatively easy and affordable to sequence. Additionally, the rapid mutation of the virus and its ability to escape antibody control fueled waves of different variants and provided a reason to follow viral genetics.
In comparison, there are many more genes of the human immune system and cellular functions that affect viral replication, with about 3.2 billion base pairs. Human studies require samples from large numbers of people, the analysis of each sample is vastly more complex, and sophisticated computer analysis often is required to make sense of the raw data. All of this takes time and large amounts of money, but important findings are beginning to emerge.
Asymptomatics
About half the people exposed to SARS-CoV-2, the virus that causes the COVID-19 disease, never develop symptoms of this disease, or their symptoms are so mild they often go unnoticed. One piece of understanding the phenomena came when researchers showed that exposure to OC43, a common coronavirus that results in symptoms of a cold, generates immune system T cells that also help protect against SARS-CoV-2.
Jill Hollenbach, an immunologist at the University of California at San Francisco, sought to identify the gene behind that immune protection. Most COVID-19 genetic studies are done with the most seriously ill patients because they are hospitalized and thus available. “But 99 percent of people who get it will never see the inside of a hospital for COVID-19,” she says. “They are home, they are not interacting with the health care system.”
Early in the pandemic, when most labs were shut down, she tapped into the National Bone Marrow Donor Program database. It contains detailed information on donor human leukocyte antigens (HLAs), key genes in the immune system that must match up between donor and recipient for successful transplants of marrow or organs. Each HLA can contain alleles, slight molecular differences in the DNA of the HLA, which can affect its function. Potential HLA combinations can number in the tens of thousands across the world, says Hollenbach, but each person has a smaller number of those possible variants.
She teamed up with the COVID-19 Citizen Science Study a smartphone-based study to track COVID-19 symptoms and outcomes, to ask persons in the bone marrow donor registry about COVID-19. The study enlisted more than 30,000 volunteers. Those volunteers already had their HLAs annotated by the registry, and 1,428 tested positive for the virus.
Analyzing five key HLAs, she found an allele in the gene HLA-B*15:01 that was significantly overrepresented in people who didn’t have any symptoms. The effect was even stronger if a person had inherited the allele from both parents; these persons were “more than eight times more likely to remain asymptomatic than persons who did not carry the genetic variant,” she says. Altogether this HLA was present in about 10 percent of the general European population but double that percentage in the asymptomatic group. Hollenbach and her colleagues were able confirm this in other different groups of patients.
What made the allele so potent against SARS-CoV-2? Part of the answer came from x-ray crystallography. A key element was the molecular shape of parts of the cold virus OC43 and SARS-CoV-2. They were virtually identical, and the allele could bind very tightly to them, present their molecular antigens to T cells, and generate an extremely potent T cell response to the viruses. And “for whatever reasons that generated a lot of memory T cells that are going to stick around for a long time,” says Hollenbach. “This T cell response is very early in infection and ramps up very quickly, even before the antibody response.”
Understanding the genetics of the immune response to SARS-CoV-2 is important because it provides clues into the conditions of T cells and antigens that support a response without any symptoms, she says. “It gives us an opportunity to think about whether this might be a vaccine design strategy.”
Dead men
A researcher at the Leibniz Institute of Virology in Hamburg Germany, Guelsah Gabriel, was drawn to a question at the other end of the COVID-19 spectrum: why men more likely to be hospitalized and die from the infection. It wasn't that men were any more likely to be exposed to the virus but more likely, how their immune system reacted to it
Several studies had noted that testosterone levels were significantly lower in men hospitalized with COVID-19. And, in general, the lower the testosterone, the worse the prognosis. A year after recovery, about 30 percent of men still had lower than normal levels of testosterone, a condition known as hypogonadism. Most of the men also had elevated levels of estradiol, a female hormone (https://pubmed.ncbi.nlm.nih.gov/34402750/).
Every cell has a sex, expressing receptors for male and female hormones on their surface. Hormones docking with these receptors affect the cells' internal function and the signals they send to other cells. The number and role of these receptors varies from tissue to tissue.
Gabriel began her search by examining whole exome sequences, the protein-coding part of the genome, for key enzymes involved in the metabolism of sex hormones. The research team quickly zeroed in on CYP19A1, an enzyme that converts testosterone to estradiol. The gene that produces this enzyme has a number of different alleles, the molecular variants that affect the enzyme's rate of metabolizing the sex hormones. One genetic variant, CYP19A1 (Thr201Met), is typically found in 6.2 percent of all people, both men and women, but remarkably, they found it in 68.7 percent of men who were hospitalized with COVID-19.
Lung surprise
Lungs are the tissue most affected in COVID-19 disease. Gabriel wondered if the virus might be affecting expression of their target gene in the lung so that it produces more of the enzyme that converts testosterone to estradiol. Studying cells in a petri dish, they saw no change in gene expression when they infected cells of lung tissue with influenza and the original SARS-CoV viruses that caused the SARS outbreak in 2002. But exposure to SARS-CoV-2, the virus responsible for COVID-19, increased gene expression up to 40-fold, Gabriel says.
Did the same thing happen in humans? Autopsy examination of patients in three different cites found that “CYP19A1 was abundantly expressed in the lungs of COVID-19 males but not those who died of other respiratory infections,” says Gabriel. This increased enzyme production led likely to higher levels of estradiol in the lungs of men, which “is highly inflammatory, damages the tissue, and can result in fibrosis or scarring that inhibits lung function and repair long after the virus itself has disappeared.” Somehow the virus had acquired the capacity to upregulate expression of CYP19A1.
Only two COVID-19 positive females showed increased expression of this gene. The menopause status of these women, or whether they were on hormone replacement therapy was not known. That could be important because female hormones have a protective effect for cardiovascular disease, which women often lose after going through menopause, especially if they don’t start hormone replacement therapy. That sex-specific protection might also extend to COVID-19 and merits further study.
The team was able to confirm their findings in golden hamsters, the animal model of choice for studying COVID-19. Testosterone levels in male animals dropped 5-fold three days after infection and began to recover as viral levels declined. CYP19A1 transcription increased up to 15-fold in the lungs of the male but not the females. The study authors wrote, “Virus replication in the male lungs was negatively associated with testosterone levels.”
The medical community studying COVID-19 has slowly come to recognize the importance of adipose tissue, or fat cells. They are known to express abundant levels of CYP19A1 and play a significant role as metabolic tissue in COVID-19. Gabriel adds, “One of the key findings of our study is that upon SARS-CoV-2 infection, the lung suddenly turns into a metabolic organ by highly expressing” CYP19A1.
She also found evidence that SARS-CoV-2 can infect the gonads of hamsters, thereby likely depressing circulating levels of sex hormones. The researchers did not have autopsy samples to confirm this in humans, but others have shown that the virus can replicate in those tissues.
A possible treatment
Back in the lab, substituting low and high doses of testosterone in SARS-COV-2 infected male hamsters had opposite effects depending on testosterone dosage used. Gabriel says that hormone levels can vary so much, depending on health status and age and even may change throughout the day, that “it probably is much better to inhibit the enzyme” produced by CYP19A1 than try to balance the hormones.
Results were better with letrozole, a drug approved to treat hypogonadism in males, which reduces estradiol levels. The drug also showed benefit in male hamsters in terms of less severe disease and faster recovery. She says more details need to be worked out in using letrozole to treat COVID-19, but they are talking with hospitals about clinical trials of the drug.
Gabriel has proposed a four hit explanation of how COVID-19 can be so deadly for men: the metabolic quartet. First is the genetic risk factor of CYP19A1 (Thr201Met), then comes SARS-CoV-2 infection that induces even greater expression of this gene and the deleterious increase of estradiol in the lung. Age-related hypogonadism and the heightened inflammation of obesity, known to affect CYP19A1 activity, are contributing factors in this deadly perfect storm of events.
Studying host genetics, says Gabriel, can reveal new mechanisms that yield promising avenues for further study. It’s also uniting different fields of science into a new, collaborative approach they’re calling “infection endocrinology,” she says.