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.”
Podcast: The future of brain health with Percy Griffin
Today's guest is Percy Griffin, director of scientific engagement for the Alzheimer’s Association, a nonprofit that’s focused on speeding up research, finding better ways to detect Alzheimer’s earlier and other approaches for reducing risk. Percy has a doctorate in molecular cell biology from Washington University, he’s led important research on Alzheimer’s, and you can find the link to his full bio in the show notes, below.
Our topic for this conversation is the present and future of the fight against dementia. Billions of dollars have been spent by the National Institutes of Health and biotechs to research new treatments for Alzheimer's and other forms of dementia, but so far there's been little to show for it. Last year, Aduhelm became the first drug to be approved by the FDA for Alzheimer’s in 20 years, but it's received a raft of bad publicity, with red flags about its effectiveness, side effects and cost.
Meanwhile, 6.5 million Americans have Alzheimer's, and this number could increase to 13 million in 2050. Listen to this conversation if you’re concerned about your own brain health, that of family members getting older, or if you’re just concerned about the future of this country with experts predicting the number people over 65 will increase dramatically in the very near future.
Listen to the Episode
Listen on Apple | Listen on Spotify | Listen on Stitcher | Listen on Amazon | Listen on Google
4:40 - We talk about the parts of Percy’s life that led to him to concentrate on working in this important area.
6:20 - He defines Alzheimer's and dementia, and discusses the key elements of communicating science.
10:20 - Percy explains why the Alzheimer’s Association has been supportive of Aduhelm, even as others have been critical.
17:58 - We talk about therapeutics under development, which ones to be excited about, and how they could be tailored to a person's own biology.
24:25 - Percy discusses funding and tradeoffs between investing more money into Alzheimer’s research compared to other intractable diseases like cancer, and new opportunities to accelerate progress, such as ARPA-H, President Biden’s proposed agency to speed up health breakthroughs.
27:24 - We talk about the social determinants of brain health. What are the pros/cons of continuing to spend massive sums of money to develop new drugs like Aduhelm versus refocusing on expanding policies to address social determinants - like better education, nutritious food and safe drinking water - that have enabled some groups more than others to enjoy improved cognition late in life.
34:18 - Percy describes his top lifestyle recommendations for protecting your mind.
37:33 - Is napping bad for the brain?
39:39 - Circadian rhythm and Alzheimer's.
42:34 - What tests can people take to check their brain health today, and which biomarkers are we making progress on?
47:25 - Percy highlights important programs run by the Alzheimer’s Association to support advances.
Show links:
** After this episode was recorded, the Centers for Medicare and Medicaid Services affirmed its decision from last June to limit coverage of Aduhelm. More here.
- Percy Griffin's bio: https://www.alz.org/manh/events/alztalks/upcoming-...
- The Alzheimer's Association's Part the Cloud program: https://alz.org/partthecloud/about-us.asp
- The paradox of dementia rates decreasing: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455342/
- The argument for focusing more resources on improving institutions and social processes for brain health: https://www.statnews.com/2021/09/23/the-brain-heal...
- Recent research on napping: https://www.ocregister.com/2022/03/25/alzheimers-s...
- The Alzheimer's Association helpline: https://www.alz.org/help-support/resources/helpline
- ALZConnected, a free online community for people affected by dementia https://www.alzconnected.org/
- TrialMatch for people with dementia and healthy volunteers to find clinical trials for Alzheimer's and other dementia: https://www.alz.org/alzheimers-dementia/research_p...
COVID-19 prompted numerous companies to reconsider their approach to the future of work. Many leaders felt reluctant about maintaining hybrid and remote work options after vaccines became widely available. Yet the emergence of dangerous COVID variants such as Omicron has shown the folly of this mindset.
To mitigate the risks of new variants and other public health threats, as well as to satisfy the desires of a large majority of employees who express a strong desire in multiple surveys for a flexible hybrid or fully remote schedule, leaders are increasingly accepting that hybrid and remote options represent the future of work. No wonder that a February 2022 survey by the Federal Reserve Bank of Richmond showed that more and more firms are offering hybrid and fully-remote work options. The firms expect to have more remote workers next year and more geographically-distributed workers.
Although hybrid and remote work mitigates public health risks, it poses another set of health concerns relevant to employee wellbeing, due to the threat of proximity bias. This term refers to the negative impact on work culture from the prospect of inequality among office-centric, hybrid, and fully remote employees.
The difference in time spent in the office leads to concerns ranging from decreased career mobility for those who spend less facetime with their supervisor to resentment building up against the staff who have the most flexibility in where to work. In fact, a January 2022 survey by the company Slack of over 10,000 knowledge workers and their leaders shows that proximity bias is the top concern – expressed by 41% of executives - about hybrid and remote work.
To address this problem requires using best practices based on cognitive science for creating a culture of “Excellence From Anywhere.” This solution is based on guidance that I developed for leaders at 17 pioneering organizations for a company culture fit for the future of work.
Protect from proximity bias via the "Excellence From Anywhere" strategy
So why haven’t firms addressed the obvious problem of proximity bias? Any reasonable external observer could predict the issues arising from differences of time spent in the office.
Unfortunately, leaders often fail to see the clear threat in front of their nose. You might have heard of black swans: low-probability, high-impact threats. Well, the opposite kind of threats are called gray rhinos: obvious dangers that we fail to see because of our mental blindspots. The scientific name for these blindspots is cognitive biases, which cause leaders to resist best practices in transitioning to a hybrid-first model.
The core idea is to get all of your workforce to pull together to achieve business outcomes: the location doesn’t matter.
Leaders can address this by focusing on a shared culture of “Excellence From Anywhere.” This term refers to a flexible organizational culture that takes into account the nature of an employee's work and promotes evaluating employees based on task completion, allowing remote work whenever possible.
Addressing Resentments Due to Proximity Bias
The “Excellence From Anywhere” strategy addresses concerns about treatment of remote workers by focusing on deliverables, regardless of where you work. Doing so also involves adopting best practices for hybrid and remote collaboration and innovation.
By valuing deliverables, collaboration, and innovation through a focus on a shared work culture of “Excellence From Anywhere,” you can instill in your employees a focus on deliverables. The core idea is to get all of your workforce to pull together to achieve business outcomes: the location doesn’t matter.
This work culture addresses concerns about fairness by reframing the conversation to focus on accomplishing shared goals, rather than the method of doing so. After all, no one wants their colleagues to have to commute out of spite.
This technique appeals to the tribal aspect of our brains. We are evolutionarily adapted to living in small tribal groups of 50-150 people. Spending different amounts of time in the office splits apart the work tribe into different tribes. However, cultivating a shared focus on business outcomes helps mitigate such divisions and create a greater sense of unity, alleviating frustrations and resentments. Doing so helps improve employee emotional wellbeing and facilitates good collaboration.
Solving the facetime concerns of proximity bias
But what about facetime with the boss? To address this problem necessitates shifting from the traditional, high-stakes, large-scale quarterly or even annual performance evaluations to much more frequent weekly or biweekly, low-stakes, brief performance evaluation through one-on-one in-person or videoconference check-ins.
Supervisees agree with their supervisor on three to five weekly or biweekly performance goals. Then, 72 hours before their check-in meeting, they send a brief report, under a page, to their boss of how they did on these goals, what challenges they faced and how they overcame them, a quantitative self-evaluation, and proposed goals for next week. Twenty-four hours before the meeting, the supervisor responds in a paragraph-long response with their initial impressions of the report.
It’s hard to tell how much any employee should worry about not being able to chat by the watercooler with their boss: knowing exactly where they stand is the key concern for employees, and they can take proactive action if they see their standing suffer.
At the one-on-one, the supervisor reinforces positive aspects of performance and coaches the supervisee on how to solve challenges better, agrees or revises the goals for next time, and affirms or revises the performance evaluation. That performance evaluation gets fed into a constant performance and promotion review system, which can replace or complement a more thorough annual evaluation.
This type of brief and frequent performance evaluation meeting ensures that the employee’s work is integrated with efforts by the supervisor’s other employees, thereby ensuring more unity in achieving business outcomes. It also mitigates concerns about facetime, since all get at least some personalized attention from their team leader. But more importantly, it addresses the underlying concerns about career mobility by giving all staff a clear indication of where they stand at all times. After all, it’s hard to tell how much any employee should worry about not being able to chat by the watercooler with their boss: knowing exactly where they stand is the key concern for employees, and they can take proactive action if they see their standing suffer.
Such best practices help integrate employees into a work culture fit for the future of work while fostering good relationships with managers. Research shows supervisor-supervisee relationships are the most critical ones for employee wellbeing, engagement, and retention.
Conclusion
You don’t have to be the CEO to implement these techniques. Lower-level leaders of small rank-and-file teams can implement these shifts within their own teams, adapting their culture and performance evaluations. And if you are a staff member rather than a leader, send this article to your supervisor and other employees at your company: start a conversation about the benefits of addressing proximity bias using such research-based best practices.