243 replies to this topic

[VP.]

Has anyone tried the $65 epigenetic aging test from Osiris Green?

 

https://www.osirisgreen.com/

 

https://www.fightagi...-to-the-public/

 

I should have some results from them in a couple of weeks.

I have. Tell me when you get your results. 

[HaplogroupW]

I used Osiris Green. I am presently unable to view my results, or get contact them;  their website generates an error when I try to do either. They are apparently in the process of switching to a new technology, as it says on their web page.

 

What I remember about my results is that they measured methylation at 3 loci. One of the three had ~20 years older than my chronological age, one about 20 years younger, and the third about my current age. With the net result estimating my age at about my chronological age.

 

I also used myDNAge service; the one using a urine sample. By contrast they measure over 500 loci. They measured my "DNAge" at 40, about 10 years younger than my chronological age.

 

For comparison, TeloYears had me at about 20 years old (about 30 years younger than my chronological age). Telomere length is mostly uncorrelated with the epigenetic clock I've heard Horvath say (I think HighDesertWind posted a ref on that topic). My employer had a local hospital that has a mobile cardiac screening service come and do tests that included blood work, ultrasonic imaging of carotid, BP, EEG and that sort of thing and it estimated my "cardiac age" at around 30 years old; that was about 4 years ago.

 

So my opinion on the older Osiris Green technique is that it produces a number with such a high variance that it's useless. N=3 loci is just too few to get a reliable number. One would expect the SWARM tech of mydnage with N>500 loci to provide better precision. The newer Osiris Green forthcoming technique might be much better.

 

This presentation was interesting on the topic. There are three speakers, the last one is Steve Horvath himself. The first is from Zymo Research whose technology is used in the mydnage service.

 

 

I think the Weidner and Wagner clock Horvath mentions at 2:01:31 in the video is the one that Osiris Green was using. I just say that because it uses only three loci, and that's the number of loci OG measured.

 

 

 

 

 

 

 

 

 

Edited by HaplogroupW, 27 March 2018 - 07:27 PM.

[Krell]

I have. Tell me when you get your results. 

 

Got an email from Osiris Green yesterday saying my results were available, but the web site was down.

Today I was able to access my account and the results are

------------

Estimated age: 59.5 years old, plus or minus 1.8 years (median absolute deviation).

 

This means that your DNA is similar to someone who is between 61.3 and 57.7 years old, according to the genes we examined.

 

 

-----------

My actual age is 73.5, so either I have selected good ancestors or clean living has paid off (Ha!).

 

Or maybe I owe it to my 2 weeks (so far) on Turnbuckle's fission/fusion protocol?  Oops guess it has been over a month

since I submitted the sample, so unless the protocol is retroactive it could not have had any effect.

 

BTW: my mother is still going strong at 97 and my father passed at 94.

 

Here are my test details:

---------

EDARADD Gene Ectodysplasia A Receptor Associated Death Domain This gene is found on human chromosome 1, and produces a protein that plays an important role in embryonic development. The protein itself is essential for proper interactions between two cell layers in a developing embryo (called the ectoderm and the mesoderm), which form the basis for many of the body's organs and tissues. Interactions between these cell layers are essential for the proper development of several bodily structures, including skin, hair, nails, teeth, and sweat glands.

---Details The sequence of DNA shown above progresses from left-to-right and top-to-bottom. Locations that are sites of DNA methylation (an epigenetic marker) are displayed in green. Any nucleotide that was not conclusively identified by DNA sequencing is displayed with a gray letter. The failure to identify nucleotides during DNA sequencing is common, especially near the beginning or end of a DNA sequence, and is a consequence of the technical process. Hover the mouse over any nucleotide for more information. The DNA used in this analysis comes from many individual cells. The percentages of methylation shown above represent the calculated percentage of DNA molecules in the sample with methylation at the indicated location. For this portion of the EDARADD gene, the nucleotides shown at positions 83 and 100 are locations of methylation that correspond with chronological age. These two position experience a decrease in the percentage of DNA methylation with age. Using only this gene, your predicted age would be 60.1 plus or minus 2.7 years (median absolute deviation).

--------------

ASPA Gene  Aspartoacylase This gene is found on human chromosome 17, and is most active in the brain where it breaks down the metabolite N-acetyl-L-aspartate into acetic acid and the amino acid aspartic acid. The production and breakdown of N-acetyl-L-aspartate appears to be critical for developing and maintaining the brain's white matter.

---Details The sequence of DNA shown above progresses from left-to-right and top-to-bottom. Locations that are sites of DNA methylation (an epigenetic marker) are displayed in green. Any nucleotide that was not conclusively identified by DNA sequencing is displayed with a gray letter. The failure to identify nucleotides during DNA sequencing is common, especially near the beginning or end of a DNA sequence, and is a consequence of the technical process. Hover the mouse over any nucleotide for more information. The DNA used in this analysis comes from many individual cells. The percentages of methylation shown above represent the calculated percentage of DNA molecules in the sample with methylation at the indicated location. For this portion of the ASPA gene, the nucleotides shown at positions 4 and 40 are locations of methylation that correspond with chronological age. These two position experience an increase in the percentage of DNA methylation with age. Using only this gene, your predicted age would be 55.9 plus or minus 8.6 years (median absolute deviation).

------------

ITGA2B Gene  Integrin Alpha 2B This gene is found on human chromosome 17, and controls the production of a receptor found in platelets that plays a crucial role in coagulation. Integrin genes also contribute to cell-surface mediated signaling.

---Details The sequence of DNA shown above progresses from left-to-right and top-to-bottom. Locations that are sites of DNA methylation (an epigenetic marker) are displayed in green. Any nucleotide that was not conclusively identified by DNA sequencing is displayed with a gray letter. The failure to identify nucleotides during DNA sequencing is common, especially near the beginning or end of a DNA sequence, and is a consequence of the technical process. Hover the mouse over any nucleotide for more information. The DNA used in this analysis comes from many individual cells. The percentages of methylation shown above represent the calculated percentage of DNA molecules in the sample with methylation at the indicated location. For this portion of the ITGA2B gene, the nucleotides shown at positions 38, 40, 54, and 92 are locations of methylation that correspond with chronological age. These two position experience a decrease in the percentage of DNA methylation with age. Using only this gene, your predicted age would be 56.1 plus or minus 7.2 years (median absolute deviation).

--------end

Edited by Krell, 05 April 2018 - 02:50 PM.

[albedo]

Has anyone tried the $65 epigenetic aging test from Osiris Green?

 

https://www.osirisgreen.com/

 

https://www.fightagi...-to-the-public/

 

I should have some results from them in a couple of weeks.

 

Just wonder if you got back results and you feel to share comments. Thank you.
 

Just wonder if you got back results and you feel to share comments. Thank you.
 

 

My apologizes Krell, I completely overlooked your last post !!

[albedo]

Got an email from Osiris Green yesterday saying my results were available, but the web site was down.

Today I was able to access my account and the results are

------------

Estimated age: 59.5 years old, plus or minus 1.8 years (median absolute deviation).

 

This means that your DNA is similar to someone who is between 61.3 and 57.7 years old, according to the genes we examined.

.....

Thank you Krell for having shared these results (and congratulations!!). I will read more carefully and study a bit the genes involved. I am only curious by now to know if by any chance, having a set of simple blood biomarkers, you have tried to compare with one of the 3 available version of Aging.AI predictors (v3.0 is the easiest one). Thank you.

 

[Krell]

Thank you Krell for having shared these results (and congratulations!!). I will read more carefully and study a bit the genes involved. I am only curious by now to know if by any chance, having a set of simple blood biomarkers, you have tried to compare with one of the 3 available version of Aging.AI predictors (v3.0 is the easiest one). Thank you.

 

No but I will put it on my TODO list.
 

[Krell]

Thank you Krell for having shared these results (and congratulations!!). I will read more carefully and study a bit the genes involved. I am only curious by now to know if by any chance, having a set of simple blood biomarkers, you have tried to compare with one of the 3 available version of Aging.AI predictors (v3.0 is the easiest one). Thank you.

 

The last blood test data that I could find was August 25 2015 when I was 70 years 9 months old (70.75yro).

 

According to Aging.Ai.30 blood test analysis:

 

Your predicted age is: 37.0 years Your predicted sex is: Male

 

 

Edited by Krell, 07 April 2018 - 11:09 PM.

[albedo]

 

The last blood test data that I could find was August 25 2015 when I was 70 years 9 months old (70.75yro).

 

According to Aging.Ai.30 blood test analysis:

 

Your predicted age is: 37.0 years Your predicted sex is: Male

 

 

 

Thank you. Difficult to interpret, as mine. At least the trend is positive. Multiple points using the same version would also be interesting. The DNA methylation test is more precise. I also bet if you dare to use the v1.0 version of aging.ai you will get a higher age prediction, it was my case at least.
 

[ceridwen]

It's obviously rubbish. It told me that I'm 11 years younger than my actual age and I've been battling dementia!

[Krell]

Thank you. Difficult to interpret, as mine. At least the trend is positive. Multiple points using the same version would also be interesting. The DNA methylation test is more precise. I also bet if you dare to use the v1.0 version of aging.ai you will get a higher age prediction, it was my case at least.
 

 

I checked v1.0 and it requires at least one entry (iron) that my previous blood tests do not cover.  Will it work with some entries blank?

[albedo]

I checked v1.0 and it requires at least one entry (iron) that my previous blood tests do not cover.  Will it work with some entries blank?

IMHO the prediction should not change much for some value lacking. Sometime I left blank or used extrapolations from other measurement I did or used a mid point in my lab ref ranges. In v1.0 they note that the markers with a ** are "Required parameter for minimal prediction accuracy of 70% within 10 year frame". In the reference paper they write: "...Many users expressed no desire to specify all 41 parameters of the blood test, so we added an option to enter only the 10 most important markers. The average number of missing values provided by the volunteer testers was 18.5 markers per person. There are several strategies for filling skipped values, including zero, mean, mode and median over all values of each marker. Evaluation of these 4 strategies on the aging.ai data showed that median filling strategy has the best performance in terms of both R² and epsilon-prediction accuracy (Figure 4C & D)."

[albedo]

I would not be so harsh as many are against aging.ai or similar tools. The authors recognize many limitations but I still believe they have a role to play when taken critically. As with everything in machine learning predictions are related to the input data quality and quantity. These predictors correspond to a huge need in the aging research and using biomarkers has an obvious convenience. Insilico has also shown evidence of link to mortality risk better than the chronological age and are working on a mortality predictor. Ideally we should also have a morbidity predictor too. More research is needed. When using the tools I also focus more on trends in time rather than absolute values.

 

DNA methylation is said to be a standard (e.g. Zymo Research) but has limitations too, IMHO. I will likely buy one of these tests and you might consider the effort which Josh Mitteldorf is very rightly promoting with LEF, see his last blog: The Mother of All Clinical Trials, Part I

 

There is a tradition of algorithmic tools to predict biological age and lot has been published. One of the best I found is the BAS (Biological Age Score of Klemera and Doubal) as described e.g. by Levine which also includes functional and other tests as pulmonary FEV, systolic blood pressure and CMV-cytomegalovirus presence). Klemera and Doubal method (KDM) was shown to reliably predicting mortality on a large cohort.

 

Levine ME. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age?. J Gerontol A Biol Sci Med Sci. 2013;68(6):667-74.

 

Edited by albedo, 10 April 2018 - 07:46 AM.

[albedo]

It's obviously rubbish. It told me that I'm 11 years younger than my actual age and I've been battling dementia!

 

I share your frustration. I wonder if you have considered also taking an epigenetic test such as DNA methylation, e.g. at Zymo Research? Steve Horvath has just developed a new test called DNAPhenoAge which links in particular to Alzheimer's disease, it "... strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease...."

https://www.biorxiv....18/03/05/276162

 

Edited by albedo, 10 April 2018 - 11:06 AM.

[brosci]

 

I think this is what you are looking for:

http://www.aging.ai/  " This is a deep-learned predictor of your age made with a deep neural network trained on hundreds of thousands anonymized human blood tests. Enter your data below and Aging.ai will guess your age and gender." 

I've used this and it said I was 39 when my real age is 56 though one of the critical blood markers was not in my panel. 

 

 

 

This is the one I think Sinclair is using. I sent in my sample yesterday. 

 

  https://www.osirisgr...roduct.php?id=1

 

https://en.wikipedia...pigenetic_clock

 

https://www.scienced...70412124358.htm

 

 

I just got around to playing with this site.  Apparently, I have the metabolic blood labs of a 25 year old.

 

 Screen Shot 2018-04-21 at 12.18.30 AM.png   76.74KB   0 downloads

 

This looks like an interesting one:  https://www.mydnage.com although, it seems like you would have to really keep track of your diet / supplements / regimen and test several times over a decade to even attempt to make some connections.

[Krell]

Has anyone tried the $299 epigenetic aging test from My DNA Age?

 

https://www.mydnage.com/

 

They take either urine or blood.

 

--------------------

Towards a Better Epigenetic Clock 
https://www.fightagi...igenetic-clock/

Researchers here report on an improved version of the epigenetic clock. A few carefully defined patterns of DNA methylation, including the original epigenetic clock, correlate quite closely with age. The current commercial implementation of the epigenetic clock, MyDNAge, has a margin of error of two years or so. While the consensus is that the clock reflects biological age, it is still the case that we might ask what exactly is being measured. The answer to that question remains to be established. It is plausible that DNA methylation changes with age are a reaction to all of the forms of cell and tissue damage that drive aging, but this is by no means certain - it could be more specific than that, tied to only some of the causes of aging.

 

QUOTE 

 

One of the major goals of geroscience research is to define "biomarkers of aging", which can be thought of as individual-level measures of aging that capture inter-individual differences in the timing of disease onset, functional decline, and death over the life course. While chronological age is arguably the strongest risk factor for aging-related death and disease, it is important to distinguish chronological time from biological aging. Individuals of the same chronological age may exhibit greatly different susceptibilities to age-related diseases and death, which is likely reflective of differences in their underlying biological aging processes. Such biomarkers of aging will be crucial to enable evaluation of interventions aimed at promoting healthier aging, by providing a measurable outcome, which unlike incidence of death and/or disease, does not require extremely long follow-up observation.

 

One potential biomarker that has gained significant interest in recent years is DNA methylation (DNAm). Chronological time has been shown to elicit predictable hypo- and hyper-methylation changes at many regions across the genome, and as a result, the first generation of DNAm based biomarkers of aging were developed to predict chronological age. The blood-based algorithm by Hannum and the multi-tissue algorithm by Horvath produce age estimates (DNAm age) that correlate with chronological age for full age range samples. Nevertheless, while the current epigenetic age estimators exhibit statistically significant associations with many age-related diseases and conditions, the effect sizes are typically small to moderate. One explanation is that using chronological age as the reference, by definition, may exclude CpG sites whose methylation patterns don't display strong time-dependent changes, but instead signal the departure of biological age from chronological age. Thus, it is important to not only capture CpG sites that display changes with chronological time, but also those that account for differences in risk and physiological status among individuals of the same chronological age.

 

Previous work by us and others have shown that "phenotypic aging measures", derived from clinical biomarkers, strongly predict differences in the risk of all-cause mortality, cause-specific mortality, physical functioning, cognitive performance measures, and facial aging among same-aged individuals. What's more, in representative population data, some of these measures have been shown to be better indicators of remaining life expectancy than chronological age, suggesting that they may be approximating individual-level differences in biological aging rates. As a result, we hypothesize that a more powerful epigenetic biomarker of aging could be developed by replacing prediction of chronological age with prediction of a surrogate measure of "phenotypic age" that, in and of itself, differentiates morbidity and mortality risk among same-age individuals.

 

Using a novel two-step method, we were successful in developing a DNAm based biomarker of aging that is highly predictive of nearly every morbidity and mortality outcome we tested. Training an epigenetic predictor of phenotypic age instead of chronological age led to substantial improvement in mortality/healthspan predictions over the first generation of DNAm based biomarkers of chronological age. In doing so, this is the first study to conclusively demonstrate that DNAm biomarkers of aging are highly predictive of cardiovascular disease and coronary heart disease. The new measure, DNAm PhenoAge, also tracks chronological age and relates to disease risk in samples other than whole blood. Finally, we find that an individual's DNAm PhenoAge, relative to his/her chronological age, is moderately heritable and is associated with activation of pro-inflammatory, interferon, DNA damage repair, transcriptional/translational signaling, and various markers of immunosenescence: a decline of naïve T cells and shortened leukocyte telomere length.

 

Edited by Krell, 29 April 2018 - 06:20 PM.

[Mind]

Want to know you biological age...for free?

 

At least with one (or two) current tests. If you are a LongeCity member, put your name into the hat!. It will be real interesting to see if the LongeCity crowd is a lot "younger" than the general population.

 

Read more about how this got started.

 

If you are not a member but would like to participate, there are some options...contact me.

[male_1978]

I think that unlike the chronological age, the biological state of the body should more be seen as a multidimensional vector. Just imagine someone who has longer than average telomeres but at the same time more epgenetic alterations. Would you call this older or younger, biologically?

 

 

Even if you discuss supplements or lifestyle factors, they might adress certain aspects of aging (like a telomerase activator), while other aspects of aging still persist. Thats why we should talk about measuring or slowing certain aspects of aging in my oppinion. 

 

 

If you calculate a "biological age number" using a resgression analysis you might even get a missleading result here, especially if someones health profile is far from the normal range or if you ignore aspects of aging you simply dont know about. Just as example, imagine a pill which boosts metabolism and thereby improves some health markers in the blood -  but also damages the mitochondria. An age marker which ignores the state of the mitochondria might lead to the conclusion that the person gets younger - while in fact he will die earlier.

 

Now let me clarify, that i am not a doctor, i just want to point out possible difficulties in this kind of measurement. What are your thoughts on this?

[albedo]

@male_1978

I tend to agree with you. To me key is the multidimensionality and the composite biomarkers measurements. Also this is where possibly machine learning technologies might help, capturing the interactions between the markers and the non linearities.

 

A bit in line with you post is the conclusion of an interesting post by Josh Mitteldorf who concludes (bold mine):

 

"...All these data in a field so new is a tribute to Horvath’s industriousness and to the promise and fruitfulness of a new methodology.

The data so far suggest that methylation programming is a big part of the driver of aging, but not the whole story.  Smoking affects life expectancy, but it doesn’t affect methylation age.  Weight loss benefits life expectancy, but it is invisible to methylation age.  Most curious are those children who fail to develop, or age prematurely, even though their methylation age is progressing on schedule.

What does it mean that radiation ages the body without advancing the methylation clock?  Perhaps that accumulation of damage is part of the phenotype of aging, though I remain hopeful that the body remains capable of undoing that damage even late in life, if it is re-programmed to want to do so.  What does it mean that AIDS advances the aging clock?  Perhaps that the immune system is a central signaling mechanism in the aging process.

So, it’s “methylation plus”.  Plus what?  Not just methylation plus damage”; though we can certainly shorten our lifespan with radiation or smoking, we can’t increase our lifespan by avoiding toxins.  “Methylation plus other epigenetic programs”—this would be my first guess.  “Methylation plus mitochondrial state” would be a close second. Methylation is all in the nucleus, and the cytoplasm of the cell seems to store independent information, and can even re-program the state of the nucleus, as suggested by parabiosis experiments. There is also evidence for“Methylation plus telomere shortening”..." 

https://joshmitteldo...lock-an-update/

[Mind]

I think that unlike the chronological age, the biological state of the body should more be seen as a multidimensional vector. Just imagine someone who has longer than average telomeres but at the same time more epgenetic alterations. Would you call this older or younger, biologically?

 

 

Even if you discuss supplements or lifestyle factors, they might adress certain aspects of aging (like a telomerase activator), while other aspects of aging still persist. Thats why we should talk about measuring or slowing certain aspects of aging in my oppinion. 

 

 

If you calculate a "biological age number" using a resgression analysis you might even get a missleading result here, especially if someones health profile is far from the normal range or if you ignore aspects of aging you simply dont know about. Just as example, imagine a pill which boosts metabolism and thereby improves some health markers in the blood -  but also damages the mitochondria. An age marker which ignores the state of the mitochondria might lead to the conclusion that the person gets younger - while in fact he will die earlier.

 

Now let me clarify, that i am not a doctor, i just want to point out possible difficulties in this kind of measurement. What are your thoughts on this?

 

Excellent point. As knowledge about aging grows, so does the field of aging biomarkers. There is unlikely to be any one test that "says it all".

 

Epigenetic changes are the best we have right now. Just a reminder that you can get a free DNA methylation test as part of a LongeCity pilot study. If you want to participate, but are not a member, contact me.

[albedo]

Expected association between inflammation and lipid biomarkers with DNA methylation accelerated aging:

 

"Our study demonstrates that epigenetic age acceleration in blood relates to inflammatory biomarkers and certain lipid classes in Caucasian individuals of the GOLDN study. Future studies should consider epigenetic age acceleration in other tissues and extend the analysis to other ethnic groups."

 

Irvin MR, Aslibekyan S, Do A, et al. Metabolic and inflammatory biomarkers are associated with epigenetic aging acceleration estimates in the GOLDN study. Clin Epigenetics. 2018;10:56.

[ceridwen]

I'm worried that I did not mark my sample clearly with my name and address

[Nate-2004]

At some point in early February or late January, I've scanned through this thread yet don't see it anywhere, someone posted a link to a PDF file showing ideal ranges to stay in as far as biomarkers like cholesterol, crp, homocysteine, etc. Does anyone know what I'm talking about or where this was?  I wish I were more mindful about bookmarking or saving links.

[pamojja]

At some point in early February or late January, I've scanned through this thread yet don't see it anywhere, someone posted a link to a PDF file showing ideal ranges to stay in as far as biomarkers like cholesterol, crp, homocysteine, etc. Does anyone know what I'm talking about or where this was?  I wish I were more mindful about bookmarking or saving links.

 

Lef has a page dedicated to optimal lab ranges: http://www.lifeexten...Testing/Page-05

 

Also Joe Cohen just created a paid for page which analyses lab tests: https://www.selfhack...er-is-now-live/

 

Though only at the beginning stage with many discrepancies to LEFs or other functional medicine practitioner optimal ranges, it could develop to something very powerful, if he will be able to fully take advantage of AI. The money to hire able people he would probably have by now.

Edited by pamojja, 06 June 2018 - 09:21 PM.

[Nate-2004]

Awesome. Also I just found the PDF I was looking for on leafscience: https://drive.google...7uG8dezDPy/view

 

My test results came in and I'm pretty good on everything except LDL cholesterol (2.8 mmol/dl) and homocysteine (8.6). I have been eating a ton of soluble fiber, drinking plenty of cocoa and taking fish oil as always lately but maybe I need other ways to get the LDL down. I normally take garlic. Maybe it was just high today when they drew my blood this morning. I just fasted for 48 hours and ate last night at 5pm. My c-reactive protein was really good, 0.20.

Edited by Nate-2004, 06 June 2018 - 09:47 PM.

[albedo]

Nate, Pamojja

 

The sites are good. You might also check out Michael Greve's blog on Functional Testing which also draw from the sites you indicate. Michael collaborates a lot with Aubrey de Grey, see last Undoing Aging Conference in Berlin last March:

 

https://brain.foreve...ctional Testing

 

Having in check the clinically relevant biomarkers is key. We likely need to focus on patterns rather than individual values and here is where deep analytics using AI will help. This mostly when you need to integrate with a lot more biomedical, locomotory, frailty, imaging data etc ... all used toward the determination of biological age and how your intervention are functioning. Epigenetics markers such as Horvath's and Levine's DNAm PhenoAge clocks have recently emerged possibly capturing a lot of both the mortality and morbidity risks. We discussed these earlier in this thread.

 

Literature is vast, I found interesting a couple of studies you might enjoy such as:

 

Extracting biological age from biomedical data via deep learning: too much of a good thing?

https://www.nature.c...598-018-23534-9

 

Protein profiling reveals consequences of lifestyle choices on predicted biological aging

https://www.nature.c...icles/srep17282

 

 

 

[pamojja]

My test results came in and I'm pretty good on everything except LDL cholesterol (2.8 mmol/dl) and homocysteine (8.6).

 
A little teaser from labtestanalyser.com:
 

Your Value: 2.8mmol/L

 

Your levels are optimal!

Optimal Range: 2 - 4.14 mmol/L

...However, studies looking at increased mortality from all causes, including heart disease, have not found a clear association with high LDL-C levels. Indeed, some studies have found that levels above the traditionally recommended amount (100 mg/dl) decrease the risk of mortality from all causes.  R, R

 

[Nate-2004]

I was wondering, is there any new tech for implantable blood monitoring chips that send all information to a phone app? Like everything I mean, from inflammatory cytokine levels to lipids to homocysteine to blood glucose and ketones at all times of a given day, even periodic A1c checks. Like, everything I got in my latest bloodwork.

 

Having that information constantly on hand would be super helpful for personalized nutrition and staying aware of what's going on.

[APBT]

I was wondering, is there any new tech for implantable blood monitoring chips that send all information to a phone app? Like everything I mean, from inflammatory cytokine levels to lipids to homocysteine to blood glucose and ketones at all times of a given day, even periodic A1c checks. Like, everything I got in my latest bloodwork.

 

Having that information constantly on hand would be super helpful for personalized nutrition and staying aware of what's going on.

 

I'm not aware of anything commercially available that checks all the boxes you mentioned.  There is this product that does continuous glucose monitoring: https://www.dexcom.com/

[sthira]

I'm not aware of anything commercially available that checks all the boxes you mentioned. There is this product that does continuous glucose monitoring: https://www.dexcom.com/

I think Geoffrey Woo (HVMN Podcast) did this or had this implanted glucose monitor similar to this. Continuous blood sugar monitoring would be fun; but like Nate, I want more markers of metabolic pathways. Which is asking a whole lot, but it'll be here eventually, no doubt. For now, basic blood panels continuously monitored, imagine how cool. Just nailing down which markers are "best" for health or lifespan extension is a huge task, obviously, and in constant flux. But nerding out on all those internal biochemistry patterns without breaking the bank or getting denied by naw-surance would be super fun and addictive.

And temptations to tinker with those systems and regulatory networks would be equally intense. Attempting to outsmart Mother Nature is tricky, of course -- just look at what we've done to the world's dammed up rivers and salt marshes, and and and... The risk is not to be minimized; but imagine being able to chart fluctuations of mTOR, or IGF-1, or free and total testosterone, inflammation markers, whatever we learn next... It's both exciting and a little terrifying -- witness our grubby little chimpanzee fingers twirlying those knobs in ignorance of longterm or downstream effects, etc etc

Edited by sthira, 17 June 2018 - 05:40 PM.

[albedo]

I was wondering, is there any new tech for implantable blood monitoring chips that send all information to a phone app? Like everything I mean, from inflammatory cytokine levels to lipids to homocysteine to blood glucose and ketones at all times of a given day, even periodic A1c checks. Like, everything I got in my latest bloodwork.

 

Having that information constantly on hand would be super helpful for personalized nutrition and staying aware of what's going on.

 

It is coming Nate. E.g. look at this presentation today (!) which unfortunately I will miss as traveling. But at least I will have a good researcher name (Prof. Azita Emami at Caltech) to follow. Good point on the personalized nutrition (see also my thread on this):

 

Medicine of the Future: Wireless Implantable and Wearable Devices

https://memento.epfl...antable-and-we/Abstract:

"Microscale implantable and wearable devices will transform the field of medicine in the near future. This talk will focus on design and implementation of miniaturized minimally invasive devices for continuous monitoring and closed-loop therapeutic systems. In particular, an implantable wireless sensor that can continuously monitor glucose level (eliminating the need for finger-pricking) will be discussed. We will show that by bringing together novel integrated circuit techniques, nanotechnology and interface engineering, small size, high sensitivity and longer lifetime can be achieved.  

In the second part of this talk, an MRI-inspired approach for precise localization and tracking of smart pills and sensors inside the body will be presented. The prototype devices called ATOMS (Addressable Transmitters Operated as Magnetic Spins) are designed to behave similar to real atoms in the body. They radiate at different frequencies depending on their location without the need for the strong magnetic field required in MRI. Our research efforts on efficient neural interfaces will be briefly discussed at the end of this talk."