Iollo (YC S22) – At-home metabolomics test to extend healthy lifespan

Hi Hacker News! We’re Dan, Jan, and Brent from iollo ( We’re developing an at-home metabolomics test that measures hundreds of “metabolites” in blood, which studies have shown can inform about health status, disease risk, dietary patterns, and physical activity. We will then provide evidence-based dietary, behavioral, and therapeutic treatments to help extend the number of years you’re disease-free (your “healthspan”).

Today’s healthcare system is reactive, meaning diseases are treated only after symptoms are present. By the time they are detected, they’re often already serious issues that require irreversible interventions, like taking lifelong medications and living with their side effects. Collectively, we end up spending trillions of dollars treating diseases reactively that can often be prevented with good health monitoring and management. Also, a lot of age-related diseases develop as a result of molecular imbalances that accumulate over years.

One scientific field where many of these molecules can be measured is called metabolomics. Having worked in this field for more than a decade, we know that the technology exists to detect potential signs of chronic conditions at the earliest stages, when they are most actionable. Dan has a PhD and did his postdoctoral research at Stanford in computational biology and metabolomics. His work covers healthspan extension, lifespan extension and machine learning-based tools for drug repurposing. Jan, who was Dan’s PhD thesis supervisor, is a professor of computational biomedicine and metabolomics at Cornell. He has published over 90 metabolomics-related papers, with a focus on age-related chronic diseases, such as cancer, type 2 diabetes, and Alzheimer’s disease. Brent was the co-founder of Circle Medical, a primary care provider via video and in-person.

The “metabolome” is defined as the complete set of small molecules found in biological organisms with a size of <1,500 Dalton, also known as metabolites [1][2]. This comprises biochemical substances such as amino acids, nucleic acids, fatty acids, vitamins, and hormones, as well as external chemicals like drugs, environmental contaminants, food additives, toxins [3][4] and metabolites produced by the gut microbiome. As of 2022, over 200,000 metabolites have been identified in nature, 40,000 of which are in blood, and over 1,500,000 are expected to still be identified (what we call the dark metabolome) [5].

The same way that fasting glucose has a baseline, other metabolites in blood, like the ~600 that we measure, also have their own baseline and deviations from these baselines have implications for your overall health and aging [6]. Compared to genetic testing, which tells people what might happen to their health, metabolomics tells us exactly what is happening in a body right now. Recent studies have shown links between blood metabolites and the risk or presence of various systemic diseases, including diabetes, heart disease, and Alzheimer’s disease; see for example [7].

Here are a few examples of what the first generation of iollo reports will include:

(1) The food a person eats and what actually ends up in their blood are not always the same thing. This is related to the concept of “bioavailability”, which differs from person to person. For example, people with impaired sugar transporters in the gut will not experience the same spike of blood sugar as people with a normal receptor (side note: this is not always a good thing, since sugars that remain in the gut lead to IBD-like problems). Our technology measures various markers of food intake, for example of red meat and plant-based diets, that can show what actually ended up in your blood. This can help guide dietary recommendations and healthy lifestyles.

(2) Your personal rate of aging. Research has shown that there is a “biological age”, which might differ from a person’s actual, chronological age. People who are biologically older than their real age tend to develop more health-related issues and age-related problems compared to people who are biologically young. Our platform will provide the users with estimates of their biological age, as well as their personal rate of aging across repeated time points and potential recommendations to slow down this rate.

(3) Our technology measures so-called “polyamines”, a group of molecules that regular lab tests do not capture today. Polyamines have been shown to improve the immune system in aging individuals, and appear to have protective properties against various diseases. Moreover, recent studies have demonstrated that a long-term, polyamine-rich diet can increase blood levels of these molecules. Hence, polyamines provide an interesting angle of dietary interventions, and the success of this intervention can be monitored with our technology.

(4) We also find some interesting, unexpected metabolites in certain people. For example in one of our pilot studies, one of our participants had a high level of phthalic acid, which can be found in plastics and cosmetics and is a chemical known to disrupt hormones in the body.

The next generation of our technology is expected to provide additional information about mental health markers, metabolic disorders, inflammation and allergies, and many more.

How it works: We send you a blood collection device, the same one we use at Stanford for research studies. After an overnight fasting period, you stick this device to your arm and press a button. A vacuum forms and a lancet (virtually!) painlessly pricks the surface of the skin to collect a small amount (~80uL) of blood over a couple of minutes. The faint feeling is similar to when you attach the new generation of glucose monitors, if you’ve ever used one. The device contains a sponge designed to stabilize the biochemical molecules in blood at room temperature. You package the device with a prepaid return label, and it gets express-shipped directly to the metabolomics lab.

As soon as we receive your sample, we store it at -80°C. Samples are defrosted, centrifuged to collect the desired blood extracts, and the extract is then dried under liquid nitrogen. These blood extracts that contain metabolites are then subjected to two different mass-spectrometry analysis step: first through an ultra-performance liquid chromatography coupled with tandem mass-spectrometry (UPLC-MS/MS), and second through a flow injection analysis tandem mass-spectrometry (FIA-MS/MS) on the same instrument to specifically extract lipids. The measured mass-spectra from the machines are then analyzed using specialized software to obtain quantification values of all metabolites.

Here is a short video of our lab process:

The resulting data is then securely sent over to us (we’re HIPAA compliant), and we perform statistical analysis and machine learning to generate an individualized report. Depending on the number of tests you do, the same procedure is repeated after a few weeks or months. This allows the user to build their own, individualized longitudinal metabolic monitoring.

We will associate metabolite profiles with wearables data, diet, supplement and medication intake, and potentially health conditions based on current research, and provide recommendations based on these.

This process also shows the difference between us and the infamous Theranos (a common question we get!) Instead of building our own machines that might end up not working, we rely on decades of research in the mass-spectrometry field and work with established metabolomics labs to ensure the quality of our measurements. Moreover, every bit of information that we communicate to the users will be heavily backed by scientific evidence which we disclose in the delivered reports.

One of the more exciting things we'll be able to do as our metabolomics database grows is to look for new signatures of age-related diseases at earlier and earlier stages. (Such analysis will only be done on de-identified data, only with consent, and only for our work towards extending healthspan.) One example of this is being able to detect early signatures of type 2 diabetes with metabolomics data, up to 12 years in advance, even when someone has a normal fasting glucose [8][9]! Once we’re able to detect these early disease signatures, it is much easier to find interventions to treat them and extend healthy lifespan, especially if they are still very early in development.

We are currently running an internal pilot and taking preorders: We will be offering a beta version to users who’ve signed up in the coming months. Tests can be pre-ordered at $50, but we won’t charge the full subscription, which is around $212-$276 per test, until your first kit is shipped to you. If you decide to pre-order, we’ll additionally provide you with your entire metabolomics data so that you can run your own association experiments. Just type in the code HNLAUNCH with your pre-order so that we can send you your data. Right now we only ship in the US.

We believe we have a real chance to change the standard of care in health while developing more understanding of human health, physiology, and aging. We hope to expand metabolomics test access to users and patients, and give providers a new way to help treat age-related diseases. We really look forward to your questions and comments and feedback!

Thanks everyone! - Dan, Jan, and Brent.

Get Top 5 Posts of the Week

best of all time best of today best of yesterday best of this week best of this month best of last month best of this year best of 2023 best of 2022 yc w24 yc s23 yc w23 yc s22 yc w22 yc s21 yc w21 yc s20 yc w20 yc s19 yc w19 yc s18 yc w18 yc all-time 3d algorithms animation android [ai] artificial-intelligence api augmented-reality big data bitcoin blockchain book bootstrap bot css c chart chess chrome extension cli command line compiler crypto covid-19 cryptography data deep learning elexir ether excel framework game git go html ios iphone java js javascript jobs kubernetes learn linux lisp mac machine-learning most successful neural net nft node optimisation parser performance privacy python raspberry pi react retro review my ruby rust saas scraper security sql tensor flow terminal travel virtual reality visualisation vue windows web3 young talents

andrey azimov by Andrey Azimov