Biotechnology
Journal

DOI 10.1002/biot.201100495

Biotechnol. J. 2012, 7, 980–991

Perspective

Quantifying your body:
A how-to guide from a systems biology perspective
Larry Smarr
University of California, San Diego, CA, USA

During the coming decade we will see an accelerated digital transformation of healthcare. Leading this change within the institutional medical community are both the move to digital medical
records and the use of digital biomedical measurement devices. In addition to this institutional
evolution, there is a non-institutional, bottom-up, unorganized, highly idiosyncratic movement by
early adopters to “quantify” their own bodies. In this article, I share my decade-long personal experience of tracking many blood and stool biomarkers, which provide insight into the health or disease of major subsystems of my body. These results are interpreted in the context of the geneticsof my human DNA and that of the microbes in my gut. Even though I am a computer scientist andnot a medical professional, by using commercially available tests and a systems biology integrative approach, I have become an early example of Leroy Hood’s vision of the emergence of predictive, preventive, personalized, and participatory (P4) medicine. It is an individual’s story illustrating how each of us can contribute to realizing this paradigm shift.

1 The digital transformation of healthcare
to a wellness paradigm
Quantifying oneself would have been only the stuffof dreams before the digital revolution. Much of thequantification can take place outside of traditional
medical environments because of the rapid drop in
the commercial cost of making time series measurements of key biological functions and of determining one’s genetic code.
Today’s ability to track and integrate health information would not have been possible without
the rise of the mass market for cell phones. As unit
shipments grew from millions to a billion per year,
the cost of all the subcomponents dropped precipitously. This has enabled the rapid growth of private
sector, foundation, and academic “wireless health”

Correspondence: Prof. Larry Smarr, University of California, San Diego,
9500 Gilman Drive, La Jolla, CA 92093–0436, USA
E-mail: lsmarr@ucsd.edu
Abbreviations: CD, Crohn’s disease; CRP, C-reactive protein; HDL, highdensity lipoprotein; IBD, inflammatory bowel disease; LDL, low-density
lipoprotein; P4, predictive, preventive, personalized, participatory; SNP,
single nucleotide polymorphism

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Received 14 DEC 2011
Revised 21 JUN 2012
Accepted 09 JUL 2012

Supporting information
available online

projects. Examples that I cover include consumer
devices that allow digital self-tracking of daily
steps, caloric burn, heart rate, sleep state, and stresslevels. The data are uploaded to the devices’ companies, who provide each consumer with their results in easy-to-understand graphical form.
In addition to external monitoring, the rapid
technological progress means that it has become
more and more economically feasible to make timeseries measurements of key biochemical variables.
Lee Hood and his colleagues believe that within thenext decade it will be possible to derive hundredsof data points from a small blood sample [1], thus
paving the way to medicine that is predictive, preventive, personalized, and participatory (i.e. P4
medicine).
The cost of human genomic sequencing has
seen an even more dramatic drop, from billions ofdollars per genome in the late 1990s to thousandsof dollars today. Sequencing of the highly variable
regions of the genome has already become a commercial commodity, and very soon the wholegenome will also be within many individuals’ economic capabilities. Combining the time series biomarkers with genomic testing can revolutionize
healthcare, by detecting diseases before symptoms
occur, providing noninvasive monitoring of dis-

© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

www.biotechnology-journal.com

Box 1: The car analogy to personalized medicine.
The paradigm shift required
to make the change from today’s medical practices tothe predictive personalized
medical care is revolutionary, but by no means unprecedented. A metaphor forthis is how radically automobile “healthcare” has been
digitally transformed over the past five decades by
Moore’s Law. In the late 1950s and 1960s, you took yourcar to the mechanic when you heard loud thumps or saw
smoke come out of the engine. When you went in withsuch a “symptom,” you invariably were told: “This is going to cost you,” since you had burned up some key partof the mechanical or electrical systems. Cars in thosedays had limited lifetimes and typically “died of a chronic failure” before you reached 100 000 miles.

As microprocessors, flash memory, and sensors exponentially decreased in cost, car manufacturers could
afford to put more electronic devices into cars to measure moment-by-moment functioning of every key subsystem. Rather than wait until you have a costly “symptom,” you now take your car into a service facility every
10 000 miles for “preventive maintenance,” during which
the car’s measurements are digitally read out and compared with a database of all other cars of the same model. Should the data be out ofrange of the “norm”, then you
get “personalized car service,” which involves a repair
on a specific set of items determined by the sensor readings. The end result is that your car at 200 000 miles runs
just as well as the day you bought it.

eases, and predicting which patients are most likely responsive to a given drug [2].
These trends will inevitably lead to a disruptive
transformation of healthcare [3]i, changing fromtoday’s “treat the chronically ill” sickness paradigm
to tomorrow’s “prevent chronic illness from developing” wellness paradigm. Obviously, this will never be a complete transformation, but as the dominant paradigm shifts, it has the potential to makeuniversal healthcare affordable [4].
This paper addresses three levels of digitalmonitoring of the body. At the highest level are themacro-variables such as nutritional input, exercise,sleep, and stress. The next layer is the traditional
systems biology approach of cross-correlating
measurements of the human genome, proteins, andmetabolic products, deduced from saliva, blood,and stool tests. The third layer, which has only
emerged in the past 5 years, is the measurement of
the human microbiome metagenome and its proteins and metabolic products, primarily throughstool tests.

maintenance check-ups (of the time series fromthe many sensors that are built into the car), tracking the body’s state through time, by wearing either
body surface or implantable sensors and by periodically giving blood, stool, or saliva samples fortests on a wide variety of molecules or microbial genetic sequences, leads to personalized preventive
medicine. Comparison between each person’s historic norms and the subpopulation with similar genetic makeup and environmental exposure allows
the early detection of “signature” perturbations associated with diseased states. These perturbations,
if left untreated, might lead to disease onset andeventual “symptoms” that often manifest only after
irreversible damage has occurred. With the aid ofadvances in pharmacogenetics and bioengineering
devices, very early detection can lead to therapies
that correct these problems, and to providing feedback about behavioral changes that can promote a
return to wellness.
As mentioned above, these technology developments are empowering a rapidly growing movement of personal quantificationii. Many have joined
the quantifiedself.com movement to learn fromeach other and organize regional meet-ups. I was
personally inspired to begin to track myself when I
read the National Geographic articlesiii on the “Experimental Man”by David Ewing Duncan [5]. In an

2 Emergence of the quantified self
movement
The radical change in how we keep our automobiles “healthy” provides an analogy to explain P4
medicine (see Box 1). Just as we take our car in fori “The Measured Man,” Atlantic Magazine July/August 2012 www.theat
lantic.com/magazine/archive/2012/07/the-measured-man/9018/© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

ii“The Measured Life,” MIT Technology Review July/August 2011(www.technologyreview.com/featured-story/424390/the-measuredlife/)
iii http://science.nationalgeographic.com/science/health-and-humanbody/human-body/chemicals-within-us/

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Image credits: © KlaraViskova – Fotolia.com, © Mechanik – Fotolia.com

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Biotechnology
JournalBiotechnol. J. 2012, 7, 980–991

Table 1. A list of consumer products of various degrees of intensity, for self-monitoring of the four pillars of health: nutrition, exercise, sleep and stressmanagement

Nutrition

Exercise

Sleep

Stress management

Entry Level

Fitbit(www.fitbit.com)
Calorie Counter(www.myfitnesspal.com)
Both use database lookup to log food andanalyze caloric intake

Omron(www.omron.com)
Pedometer to measure
steps

Fitbit,BodyMedia
Both measure thetime in wake vs.
sleep state and thecaloric burn per
minute during sleep

Meditation Oasis Apps
(Simply Being,
Rest & Relax)(www.meditationoasis.com)
Smartphone apps to help
novices to mediate

Intermediate
Level

USDA Nutrition
database(http://ndb.nal.usda.gov/)
Humanafit.com(iPhone and Android apps)
Good food database lookup,
with fat, carbohydrates,
protein. Also measures
workouts

Fitbit3D accelerometermeasures daily steps
and caloric burnPolar WearLink(www.polarusa.com)
measures heart rate andlinks to exercise equipment

Lark(www.lark.com)
Only works withApple devices. Doesn’t
measure REM amounts.
Has push notifications
for behavior
modification.

StressEraser(www.stresseraser.com)
Portable biofeedback device
for breathing and HRVa)

Advanced Level

Self Nutrition Data
(http://nutritiondata.self.com/)
CRON-O-METER(http://cronometer.com/)
In addition to calories, fat,carbohydrates, protein bothhave detailed analysis ofvitamins, nutrients, aminoacids, minerals

BodyMedia(www.bodymedia.com)
Able to sense skintemperature, galvanic
skin response, and heat
flux – also able to detect
exercises such as yoga or
free weights that do not
involve steppingZeo(www.myzeo.com)
Headband sensor
records sleep state
every 30 sec.Displays
on bedside device
and uploads to thecloudHeartmath’s EM Wave
Desktop PC(www.heartmathstore.com)
Wide range of biofeedback
modes for PC driven by
HRV pulse monitora) HRV: Heart rate variability.

era of social networks, it is not surprising that a
number of web sites (Patients Like Me, Trusera,
23andme) are available for sharing of information
amongst individuals who may have similar healthproblems or similar genetic profiles.
While there is considerable controversy about
non-medically trained people taking personal responsibility for determining the detailed state of
their own bodies and then making behavioral
changes to achieve personal goals, it is unlikely that
this trend will reverse. There are a number of powerful cultural forces driving this phenomenon: individual reaction against the U.S. obesity epidemic[6]iv, a healthcare system in which the average
American gets less than 1 hour per year with theirdoctor, the widespread fascination with personalgadgets, a growing number of “apps” for our smart
phones that enable personal tracking, and social
network-enabled peer pressures to personally improve our own health.

3 External body tracking: The four pillars ofhealthWhat many consider [7, 8] to be the four “pillars ofhealth” – nutrition, exercise, stress management,
and sleep – can all be measured and tracked with agrowing variety of consumer products (see someexamples in Table 1). Most people can improvetheir overall health by using the biofeedback thatthese sensor systems produce to alter theirlifestyle.

3.1 Nutrition
One of the major drivers of quantified health overthe past decade has been weight loss through nutritional change.v While most people engage inweight loss through calorie counting, it should be
noted that the nutritional profile of the food you
v For the books I have found most useful for keeping me healthy and foriv

www.cdc.gov/obesity/data/trends.html

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my own nutrition program see http://lsmarr.calit2.net/repository/LS_
reading_recommendations_FiRe_2011.pdf and www.xconomy.com/sandiego/2010/05/12/how-internet-pioneer-larry-smarr-lost-20-pounds-bybecoming-a-quantified-self© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Biotechnol. J. 2012, 7, 980–991

consume is equally important. Besides calories, one
should measure the amount of protein, carbohydrates, and fats. It is also important to track theamount of fiber, sugar, and sodium. Ideally, one
would like to track the amino acid spectrum (particularly important for vegetarians), the ratio ofomega-3 to omega-6 essential fatty acids, and thevitamin, mineral, and micronutrients (see Table 1).
In my case, I took 12 days in which I ate at homeand measured every gram or fluid milliliter of every
ingredient, then used the nutrition tables provided
by the US Department of Agriculture to convert tocalories and to, grams of protein, carbohydrates,
fats, sugar, sodium, and fiber. Putting all this in a
spreadsheet and averaging over the 12 days ofmany different food types gave me a fairly accurate
snapshotvi of what I was putting into my body.
The bathroom scale is one of the simplest andmost effective ways of self-monitoring. You should
weigh yourself at the same time once per day or per
week and record the data over a year or morevii. It
is thought to be best to lose weight slowly so thatthe body can have time to adapt all its internal biochemical cycles to the new equilibrium. I lost
25 pounds over 5 yearsviii, or ~1 pound every
10 weeks, through regulating my diet and exercise
levels.
In addition to the body mass index (BMI)ix, there
are various ways to measure the relative change inpercentage of body fat over time: calipers for apinch of skin at the neck, chest, and thighsx, weightscales with electrical currents that go through thebody, immersion techniques, etc. Tracking this relative measure shows that you lose body fat at different rates from different parts of your body. However, accurately determining your total body fat ismore difficult. The best way is to have a full bodyscanxi, which gives the 2D distribution of your bodywww.biotechnology-journal.com

fat and then integrates to come up with an absolute
number.

3.2 Exercise
Measuring the daily caloric burn from exercise is
the complement to measuring caloric intake. Not
only does exercise reduce your future chance of
cardiovascular disease [9] and reduce stress, it also
releases a number of biochemicals, such as endorphins, serotonin, and neuron growth factor.
Walking is one of the simplest forms of exercise
with health benefits of reduction in cardiovasculardisease [10], so a number of commercial devices
are available for measuring your daily steps. But it
is important for your sustained health to measure
the amount of time you spend in aerobic exercise,since the latter has many health benefits [11, 12].
Using a variety of consumer electronic products,
one can measure the daily number of steps, stairs
climbed, and caloric burn (see Table 1). Using aheart rate monitor, which wirelessly couples to exercise machines, you can adjust your exercise pattern so as to make a desired portion of your caloric
burn aerobic.
Complementary to walking or aerobic exercise,
resistance training builds lean body mass and isalso critical for avoiding cardiovascular disease[13]. The extra muscle cells contain more [14] of thecellular “power stations,” called mitochondria,
which raise your overall metabolism. In addition tomeasuring your heart rate while exercising, it isalso important to track your blood pressure, pulse,
and resting heart rate, since high blood pressure iscorrelated [15] with increased risk of cardiovascular disease. There are a number of accurate consumer blood pressure monitors. Ideally, losing
weight, gaining strength, regularly exercising, andlowering stress should lower your blood pressure
and resting heart ratexii.

vi

For the results see Table 1 in my article “A 10-year detective story ofdigitally enabled genomic medicine” http://lsmarr.calit2.net/
repository/092811_Special_Letter,_Smarr.final.pdf (hereafter referred
to as “LS-SNS”)
vii Many weight scales now have Bluetooth wireless connections from thescale to your personal computer so it is easy to create a time series ofyour weight.
viii See slide 14 of my presentation at http://lsmarr.calit2.net/
presentations?slideshow=10522344
ix For a BMI calculator see e.g. www.mayoclinic.com/health/bmicalculator/NU00597. For instance, in my case in the 6 years in which I
dropped 25 pounds (2000–2006), I dropped from a BMI of 27 (overweight) to one of 23.6 (high normal) in 2006.
x See slide 8 of my presentation at http://lsmarr.calit2.net/presentations?slideshow=5394995. These relative measurements would indicatethat by 2006 I had lost 1/3 of my body fat in 2000.
xi I use the GE Lunar DXA flatbed densitometry scanner, which we havein the Calit2 Exercise and Physical Activity Resources Center© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

3.3 Sleep
While many people may track their body’s performance when they are awake, many do not think
about monitoring the sleeping period, in which we
spend more than a quarter of our lives. Spending anight in a sleep lab is still the only accurate way tomeasure all the aspects of the sleep state; however,these days, there are also consumer products
emerging that approximate the sleep lab experi-

xii My resting heart rate fell from the mid-60s to the low-40s. I measured

my blood pressure daily for a month with an average of 134/73 and an
average pulse of 55.

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Journalence with just a simple headband sensor or device
you wear on your arm (see Table 1). Since the body
carries out much of its physical and mental maintenance during sleep, having good sleep quality
and quantity is very important to your health [16].
However, for the great majority of people who do
not track the details of their sleep, this part of theirlife is unknownxiii. As in nutrition, exercise, andstress measurements, the biofeedback enables you
to change behavior and “tune” your body to ahealthier state – in my case, I’ve made a conscious
effort to increase my sleep to 8 hours per day.

3.4 Stress reduction
Stress reduction is perhaps the least understoodaspect of increasing your quality of life and reducing future disease states. Stress is directly translated into the body’s biochemical systems [17]. Thereexists a very strong brain-gut neural connection(the colon is the most enervated organ in the bodyoutside the brain) with major impacts on yourhealth [18]. Stress can even alter your gut microbial
ecology through the brain-gut-enteric microbiota
axis [19].
There are a variety of methods (see Table 1) for
modification of your stress level through biofeedback. Besides meditation, there is a quantitative
method for measuring and reducing stress using
your heart rate variation, measured by the series ofabsolute time intervals between heart beats. Usinga pulse sensor coupled to a PC user interface, software allows one to measure and modify the dynamics of the sympathetic and parasympathetic
nervous systems. This quantifies [20] (This field istermed “Heart Math”) many states of human emotion, extending the quantified self from the physical regime into the psychological and emotional.

4 Internal body biomarker tracking
As we move from tracking the body from the outside to tracking biomarkers inside the body, wemove into the realm of systems biology applied to
medicine, as articulated by Hood and colleagues[21, 22]. The vision is that with the complete knowledge of the individual’s genomic code and its variations across the population, combined with massive amounts of data on proteins (via proteomics)

xiii I have worn a Zeo sleep sensor headband for over 400 nights. I discov-ered that according to Zeo ~50% of my sleep is in REM, over twice thatof the average 60-year-old American male in the Zeo database, eventhough my total time in deep sleep is about the same.

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and metabolic products (via metabolomics), we candetermine the state of major biochemical subsystems in the body and monitor their time evolution.
Here I discuss my experiences in applying this systems approach to my own health.

4.1 Blood biomarker tracking
The blood system has long been known as a powerful “window” into the state of many of the major
subsystems of the body. Currently, I track over one
hundred variables (both molecules and blood cell
types) in my blood with a time frequency of several months to several years. In the following sections, I organize these tests into the major subsystems of the body that are probed by the blood tests.
My goal is to give an overview (for details see Supporting information) of what is possible in thisbody surveillance mode and to illustrate each with
my own personal results.
My major conclusion is that most of the blood
variables turn out to fluctuate within their normal
ranges, but by tracking a large number of variables
and using one’s own historical data as an internal
control, one can easily detect those few variables
that are out of range and use that information togradually home in on the underlying dysfunction in
the body.

4.1.1 Measuring what to supplement
We can adjust the concentration of a variety of elements and molecules in our blood through food or
supplements. By measuring their levels, we can determine if we need to alter our intakes. For instance, standard blood tests provide electrolyte levels; besides the common electrolytes (e.g. sodium,
potassium, calcium, magnesium, etc.), I also test forthe micronutrients that are essential for health(such as arsenic, chromium, cobalt, copper, etc.). In
my case, blood tests revealed that my levels ofchromium, copper, magnesium, molybdenum, andselenium were lower than optimal; therefore, I am
taking supplements to bring them back up. I also
test for a variety of nonessential elements in the
blood and stool that can indicate adverse environmental exposures.
Equally essential to electrolytes and micronutrients are the levels of key vitamins and antioxidants.
While consuming a diet rich in both is necessary,
this does not always translate into adequate
amounts in the blood. For instance, most Americans
are deficient in vitamin D, which can be easily tested for [23]. Another problem, also not widely recognized, is that taking prescription drugs or evencommon foods such as grapefruit and garlic can alter the absorption of many biochemicals – for ex-© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Biotechnol. J. 2012, 7, 980–991

ample, the statin I take interferes with the body’s
synthesis of coenzyme Q10, an important component of the body’s energy cycle. I therefore takesupplements to counteract this effect. This is anarea where asking the prescribing physician about
possible needs for supplements can be beneficial.

4.1.2 Blood cell system
The blood cell system contains many clues about
your body’s health. A complete blood count (CBC)quantifies your white and red blood systems. It will
give the white blood cell (WBC) count, which canrise if you have an infection, as well as the percentage of each of the five different types of whiteblood cells. The CBC also quantifies the red blood
cells (RBCs), as well as several other parameters.
Finally, a CBC also measures the platelet count andthe mean platelet volume. Given the key role of the
RBC in delivering oxygen throughout the body, theiron complex is closely associated with the healthof the RBCs.The hemoglobin molecular complex
has a heme molecule which has a central iron atomand contains the oxygen atoms. To get a profile ofthe iron sector, one needs to measure levels of iron,ferritin, vitamin B12 and folate (needed to makeRBCs) once or more times per year, as well as theiron-binding capacity.

4.1.3 Blood sugar system
The glucose-insulin system controls blood sugar
levels. High blood glucose promotes production of
insulin by the pancreas. Insulin stimulates fats,muscles, and the liver to take up more glucose, thus
bringing the blood-glucose concentration backdown. Low blood-glucose promotes the productionof glucagon, which stimulates release of glucose
into the blood by storage tissues, and also induces
hunger. The pursuit of a healthy nutritional dietleads directly to a focus on the body’s glucose-insulin cycle [24]. Since I was initially diagnosed as
pre-diabetic, I have repeatedly measured my glucose and insulin with fasting blood tests (see Supporting information) and have also taken a glucose
tolerance test to look for insulin resistance.

4.1.4 Hormone system
Hormones provide the body with a messaging system, in which chemicals produced in the endocrine
glands travel through the blood stream to otherparts of the body, which adapt when they receive
the hormone signals. Therefore, the health of thesesystems is critical since, if the hormones are notproduced at the correct level, there can be a cascade of chemical changes throughout the body. For
instance, the thyroid gland hormones, which are responsible for controlling metabolism in the cells in© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

www.biotechnology-journal.com

your body and which influence a number of otherhormonal systems, can be measured. A number ofhormones are tied to changes in our stress levels.
Cortisol is one of the primary hormones producedby the adrenal endocrine glands and is intimately
related to how your body handles stress. I found,using a saliva test, that I may have a depleted reserve of cortisol probably caused by living for too
many decades under high stress. Since other hormones, such as testosterone, are lowered understress, I also tested my testosterone level. Given
these results, I am beginning to use some of thestress reduction techniques described above.

4.1.5 Liver and kidneys
The liver is one of the most complex biochemical
processing organs in the body. It is responsible fordetoxification of the blood and metabolizing food,alcohol, and medications. There are blood tests tomonitor key liver enzymes, such as aspartatetransaminase (AST), alanine transaminase (ALT),
and alkaline phosphatase (ALK). My values havetypically been within the normal range, except
when I was on the prescription drug prednisone, inwhich case AST and ALT jumped above the upper
limit and ALK dropped below its lower limit. All
three reverted to normal ranges when I stopped
taking the medication.
Similarly, the kidneys filter your blood to remove wastes, producing about 2 L per day out of~200 L of blood processed. Given the high throughput of the kidneys, it is important to monitor kidney
function and protein metabolism over time, using
standard tests including blood urea nitrogen(BUN), creatinine, and uric acid.

4.1.6 Cardiovascular system
Coronary heart disease (CHD), the leading cause ofdeath in the United States, often develops from thebuildup of plaque in the coronary arteries. There
are several imaging modalities available to measure this buildup, including multi-slice CT heartscans and whole body CT scans. In addition to visualizing the coronary arteries, the device computes a “coronary artery calcium score”, which canhelp predict your risk of future heart attack [25]xiv.
Since my father died of congestive heart failure,
brought on by major blockage of his coronary arteries, I have had both imaging modalities to see
whether I am in danger of developing this debilitating disease.

xiv

CAC over 100 indicates significant amounts of hard plaque in thecoronary arteries. In July 2007 my CAC was 7.

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Table 2. My cholesterol levels before and after regular use of statins

Cholesterol variable

Recommended

Mine before statin

Mine after statin

LDL
LDL subclass pattern
HDL
TGa)
TG/HDL
Apolipoprotein B
Lipoprotein(a)<130 mg/dL
A>40 mg/dL<150 mg/dL<2<110 mg/dL<10 mg/dL

100
A/B
50
62
1.2
80
11

45
A
70
35
0.5
46
4

a) TG, triglyceride

Several blood variables can also be measured todetermine your likelihood of developing moreplaque in the future. A variety of lipids and lipoproteins are often used to evaluate future risk for cardiovascular disease. The most accurate blood test is
the vertical auto profile (VAP), which yields a number of predictive biomarkers for future heart disease. The most readily available tests are for LDL(“bad”), HDL (“good”) cholesterol, and total cholesterol. However, several other quantities have ahigher correlation with future heart disease thanthese three commonly followed markers. The ratioof triglycerides to HDL has been found to be one of
the most powerful single lipid predictors of futureheart disease [26]. Similarly, apolipoprotein B, another VAP test result, has more predictive power
for future heart disease [27] than LDL. Finally,
lipoprotein(a) is part of a VAP test, but it is more
weakly associated [28] with future heart disease.
Therefore, changing these variables to healthier values has become a goal of medicine. One classof the most widely used pharmaceuticals to achieve
this goal are thestatins [29], although this remains
a controversial topic. I have found tracking all of
the variables mentioned above that the use ofstatins certainly improves my values of these variables (see Table 2).

4.1.7 Inflammation
Inflammation has become widespread in Americans, enhancing the likelihood of a wide range ofchronic diseases [30]. A major driver of this “inflammation epidemic” is the overconsumption offoods rich in omega-6 essential fatty acids rather
than in omega-3s [31]. The ratio of intake of omega6 to omega-3 drives the eicosanoid hormonal signaling system, which exerts control over the vascular system [32], inflammation, and the immune system.
A number of diets stress the need to avoid thetypical American ratio [33] of nearly 20:1 omega-6
to omega-3 and bring it closer to ~2:1, which is whathunter-gatherers have and therefore the food in-986

take regime under which most of our genetics
evolved. High values of omega-3s in the blood arecorrelated with lowering [34] the risk of futureheart disease, as is a low omega-6 to omega-3 blood
serum ratio [35]. By altering my diet to reduce intake of omega-6, adding foods rich in omega-3s,
and supplementing daily with omega-3 fish oil
pills, I found that I had moved to very good values(see Supporting information), indicating that I had
minimized inflammation-driving components frommy food.
The sources of inflammation, however, aremuch more varied than the food we consume. It canalso be driven by infections or autoimmune diseases. Therefore, it is important to measure yourserum inflammation level directly. The most widely used biomarker is complex reactive protein(CRP). A high CRP indicates an increased risk ofcardiovascular disease [36]. In fact, research has
shown that high CRP is a stronger indicator of future cardiovascular events than LDL cholesterol[37]. That is, even if you have a low LDL, if you havea chronic elevated CRP, you have increased risk of
future heart disease [38].
To my surprise I found that over the past 6 years,
my CRP level was chronically elevated (seeTable 3), so much so that I am in the high risk category for future heart disease and diabetes [39]xv.
This high level of inflammation was confirmed by
two other blood serum inflammation biomarkers –the sedimentation rate and the levels of lipoprotein-associated phospholipase A2 (Lp-PLA2).
One possible source of inflammation is allergies
to specific foods or airborne irritants. To determine
whether the high value of my chronic inflammation
was caused by this, I took several blood tests tocheck for elevated blood levels of immunoglobulin
E (IgE). The tests looked for blood antibodies

xv A CRP greater than 3 mg/L puts one in the high risk category for futureheart attacks, and increases the odds of developing diabetes by 4–6×
[39]. My CRP peaked at 27 mg/L in January 2012.

© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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Table 3. My values of key inflammation and immunology variables

Blood:
CRP
Stool:
lactoferrin
calprotectinlyzosymesIgA

Normal upper limit

My high value

Multiple of upper limit

1.0 mg/L

27 mg/L

27×

7 μg/mL
50 μg/g
600 ng/mL
200 mg/dL

900 μg/mL2500 μg/g
1200 ng/mL
1300 mg/dL

128×
50×
2×
6.5×

against over 100 foods and 36 airborne pollens. The
results were 100% negative for all substances tested. These tests showed I do not have an acute reaction to the foods tested, it is likely that my chronic
inflammation is not a result of allergies.
In summary, by blood tracking, I discovered that
I had a persistent source of inflammation in mybody, which could lead over time to cardiovasculardisease. Given that this inflammation was not driven by my omega-6/omega-3 food intake or by allergies, what was the source of the chronic inflammation? To answer that question, I began to quantify another system, complementary to the blood.

4.2 Stool biomarker tracking
The gastrointestinal tract, while tightly coupled tothe circulatory system, provides an important second window on your health. The colon contains ten
times as many microbial cells as the number of human body cells, and is also the site of the majorityof immune cells in the body. Commercial stool tests
can probe the state of the microbial ecology, aspectsof the innate and adaptive immune systems, andwhether you are in an inflamed state, by measuring
a variety of proteins. Specifically, lactoferrin is a
glycoprotein shed from the surface of white blood
cells (the most common type, neutrophils) as they
respond to intestinal inflammation. Calprotectin is
another protein associated with neutrophils.
Lysozyme is an anti-bacterial enzyme secreted aspart of the innate immune system. Finally, secretory immunoglobulin A (sIgA) is the principal antibody protein in the first line of mucosal adaptive
immune defense.
In 2008 I began having several stool samples per
year tested using Your Future Health (YFH) Blood
Testing Company’s Comprehensive Stool Test.
What I discovered is summarized in Table 3. Although episodic, all four of the colon protein biomarkers were reaching quite elevated values compared to the normal expected range, confirmingthat the source of the inflammation measured by
the CRP and sedimentation rate in my blood was© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

likely in the colon. High values of both lactoferrin
and calprotectin have been shown to be differentiators between inflammatory bowel disease (IBD),a chronic incurable autoimmune disease, and irritable bowel syndrome (IBS) and other forms of colitis [40]. Furthermore, my peak lactoferrin and calprotectin values were comparable with values associated with people suffering from active IBD (seeFig. 1 in [41] and Fig. 2 in [42]).
Based on the high values of these biomarkers
and images and biopsies from a colonoscopy, thediagnosis emerged that I have late-onset Crohn’sdisease (CD), which along with ulcerative colitis(UC) are the two forms of IBD. Less than 5% of patients with CD are detected after age 60 [43], so thiswas a fairly rare phenomenon. However,by looking
at a variety of blood and stool markers, it was easily detected by their extreme values (Table 3) several years before I began to have acute symptoms of
CD. Also looking at the time series that I made ofthese markers revealed the episodic flares that arecharacteristic of IBD [44]xvi. The final confirmation
was provided by MRI and CT imaging studies,
which in 2011 definitively concludedxvii that the inflammation was confined to ~16 cm of my sigmoid
colon.

5 Genomics
The pathogenesis of IBD (and often other autoimmune diseases) involves a genomic predisposition
and an interaction with environmental factors[45], particularly those generated by our gut microbiome. For this reason, I expanded my quantification from time series of blood and stool biomarkers
to genomic sequencing.

xvi
xvii

www.techlab.com/docs/posters/s1423_print.pdf.
My physician is Dr. William J. Sandborn,Chief, Division of Gastroenterology & Professor of Medicine, UC San Diego

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Journal5.1 Human genome

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What I have discussed so far has been focused on
the human cells in the body. But research has revealed that our human cells representonly 10% of
the total cells in our “superorganism.” Bacteria occur over all of the body’s outer surfaces, which include not only the skin, but the entire GI tract, theears and sinus cavities, and the urogenital tracts(see the special issue on the gut micrbiota in Science [47] and articles in Nature [48-50]). The great
majority of these bacterial cells reside in the large
intestine, possessing over 100 times the number ofgenes as human DNA. This makes the complex interactions between the human and microbe sys-

tems in the gut one of the most significant interfaces in the body [47].
Bacteria account for over 50% (by dry weight) of
human stool [51]. Several groups of gut microbes
can be cultured from stool tests, including Bifidobacterium, Lactobacillus, Escherichia coli, Enterococcus, Bacteroides fraglis group, and Clostridium
species. Using the YFH stool tests that detected myhigh values of lactoferrin, I tracked the value ofthese bacteria groups over the past 4 yearsxix.
I found that after I was prescribed a 10-day courseof antibiotics in September 2008, it took 2–3 years
for the populations of “good” bacteria to fully recover [52], and the values have fluctuated since. In
the meantime, a wide range of “bad” bacteria
showed up in the cultures at high levels. It may wellbe that my use of antibiotics in 2008 was related to
my developing full CD symptoms in 2011, sincesimilar delayed reactions have been reported [53].
Although tracking the composition of the gut
bacterial community that can be cultured yields
some insights, studying the complete interactive
human/microbial system was quite difficult until
6 years ago, because some three quarters of thebacterial species are anaerobic and, therefore, noteasily cultured. Since 2005, the rapid decrease in
the cost of genetic sequencing methods has made amuch more complete mode of analyzing the ecology of colonic bacteria possible. Several sequencing
techniques can be used to delve into this complex
system.
Autoimmune diseases such as IBD significantly
disrupt the gut microbiome [54]. To see whether I
have the major biodiversity collapse and missing
genes that have been reported in CD patients, in2012 I am having both phylogenomic and metagenomic sequencing carried out on my gut microbiome by the J. Craig Venter Institute in Maryland, withthe computational analysis done at UCSD.
It may well be that CD can be stratified into several different diseases by looking at the human andmicrobial genetics and metabolic biomarkers to determine the physical basis for the disease. Heretofore attempts to define subpopulations of CD havebeen based on location of the inflammation or
severity of symptoms [55]. However, it has beenshown that there is disease stratification determined by the gut microbial ecology. Whereas commercial stool sample tests track only a few bacterial metabolites, researchers use mass spectrometry
to carry out a complete metabolomic analysis of thegut microbiome. One result shows that CD that is
localized in the ileum (ICD) can be clearly distin-

xviii

xix

In the middle of the past decade, several consumer
companies (e.g. 23andme and Navigenics) beganproviding inexpensive saliva genetic sequencing
services for one’s single nucleotide polymorphisms(SNPs), the million or so bases along your DNA in
which at least 1% of the human population has genetic variations. SNPs cover ~90% of all genetic
variation among humans. Recently, exome sequencing of the 50 million bases that are part of thehuman gene coding regions began to be offered by
23andme for $1000 on a limited basis. However, thecost of obtaining a complete human genome(diploid DNA has 6 billion bases) is $10 000 or lessper person sequenced in 2011. Estimates are that inless than 5 years there will be over 1 million full human genomes sequenced every year for prices
comparable to today’s exome sequencing. It seems
likely that as the price of sequencing the full human genome falls below $1000 over the next
decade, it will become a standard procedure.
Knowing that CD was an autoimmune disease,
I searched 23andme for “Crohn’s” and discoveredthat I had SNPxviii rs1004819, which from genomewide association studies (GWAS) puts me at 80%
higher risk for CD than the general population.
This SNP was in the interleukin-23 receptor gene,which is associated with pro-inflammation. So I
clearly had the “genetic predisposition” to CD,
which was likely the long-sought source of inflammation that was chronically elevating my CRP, inspite of my anti-inflammatory nutrition. However,
IBD seems to be co-created [46] by the host genetic polymorphism and disturbances in the colonicmicrobiome, so I now turned my attention to the genetic structure of my gut microbiome.

5.2 Gut metagenome

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See Figure 15 in LS-SNS

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Biotechnol. J. 2012, 7, 980–991

guished from CD localized to the colon (CCD) via
the different microbial metabolic signatures [56]xx.
Presumably, this difference in microbial metabolic products implies a different species diversity
in these two cases. This has been verified [57] in a
recent study of CD in twins who shows clear differences in the gut microbial species diversity in ICD
and CCD. The logical conclusion is that ICD and
CCD are different subtypes of the CD disease. Similarly, from the human DNA, the SNP GWAS havefound a number of different human DNA polymorphisms in genes associated with different portionsof the immune system. Some of these SNPs are correlated with ICD (see Fig. 1 in [58]).
Clinical trials are needed in which the phenotyping of the disease is correlated with these genetic and metabolic biomarkers to see if such disease stratifications are robust. In the near future, it
should be possible to determine if these systems
biology approaches to disease state definition andevolution can lead to more effective therapies, specific to the disease subtype, for minimizing thesymptoms or even reversing the autoimmune diseases.

6 Systems biology of the superorganism
6.1 The personal omics profile
The systems biology vision requires high resolution determination of four major data components:
genomics, transcriptomics, proteomics, and metabolomics (including lipidomics) of the individual.
These can then be combined (see Fig. 1 in [59]) withimaging modalities and clinical records to support
personalized medicine. The human genomics canbe resolved at different levels: the roughly million
bases at which 90% of human variation occurs(SNPs), the ~100 million bases which code forgenes (exons), or at 6 billion bases (full diploid
genome). The DNA expresses itself in specific locations and times through RNA, which can be sequenced, yielding “transcriptomics”. Mass spectrometry enables “proteomics” in which the proteins derived from the DNA genes can be discovered, although these are also post-genomicallyaltered. Finally, using mass spectrometry, the small
molecules that are formed by the body’s metabolism can be determined, “metabolomics”. This
metabolome includes a subset of fats (lipids) whose
measurement yields “lipodomics” [60].

xx I have submitted a stool sample to Jansson’s team for metabolomic

analysis to see if my colon-localized CD agrees with this research.

© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

www.biotechnology-journal.com

In conclusion, my personal research has revealed that even at the SNP resolution of the human genome, combined with time series of a few
proteins and metabolic biomarkers for which there
are commercially available tests, one can detect
disease before it fully manifests itself with symptoms. Further, the biomarker time series provides amuch more accurate picture of the evolution of thedisease state than is possible by monitoring symptoms.
With the development of high-throughput laboratory techniques, the research frontier – using
this same methodology, but with 1000× the numberof data points in each sector than I used –can gain
an early glimpse of the power of P4 medicine. A recent paper [61] illustrated this. Stanford geneticist
Michael Snyder and his colleagues were able to resolve his complete genome at ultra-high resolution(140× coverage), and, over the course of 2 years,
took blood samples about every month from which
they derived his complete transcriptomics, proteomics, and metabolomics. As a result, he was able
to track the alteration of these systems over time as
he battled two viral attacks. He found that he had agenetic predisposition to type II diabetes and during one of the virus attacks he actually saw the disease begin to switch on. However, at present, thistour-de-force illustration of the future vision ofsystems biology can only be carried out in a major
academic research laboratory. With decreasing
costs something similar may become clinically possible within 10 years.

6.2 Beyond the personal omics profile
The next step is to expand Snyder’s experiment toinclude the full human microbiome, so that one isstudying the systems biology of the superorganism[62] and not just the human cells. This means thatthe genomics needs to include both the full humangenome and the time varying microbial genome
across the body’s surface. The transcriptomics will
be a combination of the transcripts of both humanand the microbialRNA. This would be similar forthe combined proteomics and metabolomics
datasets. Researchers are already engaged in carrying out parts of this program. For instance, thestudy of the combined metabolic products of ourhuman and microbial cells is termed “metabonomics” [63].
One breakthrough that this approach could lead
to is the elucidation of the pathogenesis of autoimmune diseases. Given a specified genetic predisposition to such a disease, one should be able, bytracking the time evolution of the ecological diversity and metabolic products of the microbiome

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Journalalong with human biomarkers, to unravel the seriesof events in which the host genetic SNP predisposition to autoimmunity translates into an alteration[64] of the gut microbial ecology and the onset ofthe autoimmune disease with its eventual symptoms.

Biotechnol. J. 2012, 7, 980–991

Larry Smarr is the founding Director of
the California Institute for Telecommunications and Information Technology(Calit2), a UCSD/UCI partnership andthe Harry E. Gruber professor in
UCSD’s Department of Computer

7 Summary
Body quantification can be divided into two major
sectors – macro non-invasive measurements andmicro internal measurements. By comparison of
one’s own time series with population norms, it canbecome clear when a variable is far out of range.
The greatest insight seems to come from multivariant analysis involving several variables fromdifferent sources that have abnormal values. The
example here of diagnosing my colonic CD camefrom observing that blood CRP, stool lactoferrin
and calprotectin, colon microbe abundance, and a
specific SNP all had abnormal values. This was
confirmed by multiple body imaging modalities.
It would seem that this quantified-self approach
will lead naturally to systems biology approaches.
In particular, there seems to be a clear opportunity
to build a systems model of the joint gene expression of the host and microbial DNA in the colon tosee how major excursions from equilibrium can occur. As we gain a better understanding of the physical basis of disease states via systems biology, a
new taxonomy of diseases will emerge, based on
the genetic predisposition and underlying physicalsystem changes over time, which will complement
or even eventually replace the time-honored approach of disease classification from symptoms.
Such a science-based disease classification should
lead to much more personalized and effective therapies.
Conflict of interest: The author is a member of the
Scientific Advisory Board of Complete Genomics, Inc.

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