There’s Always a Bigger Fish

A Rapidly Changing Fish Market

Like poultry, pork, and beef, seafood is a source of protein.  But, unlike the other three categories of animal flesh that are consumed as food, there is far more variety among fish than chickens, pigs, or cattle.  This is largely because many fish are still wild-caught from the oceans.  But that’s not as true as it used to be; the majority of fish on the market are now produced by aquaculture (i.e. farm-raised), and the percentage of aquaculture seafood on the market is expected to increase as declining stocks of wild-caught fish are replaced with those that are farm-raised.  Major species raised by aquaculture include catfish, crawfish, mussels, salmon, scallops, shrimp, tilapia, and trout (FAO, 2016).   But, even though there are many varieties of seafood raised as aquaculture, there still are many more different varieties that are wild caught.

For the purposes of a discussion of the pluses and minuses of consuming fish while pregnant, there are two main characteristics of fish that are of interest.  The first is methylmercury.  Even though some methylmercury can be found in just about all seafood, the amount varies tremendously.  Since it bioaccumulates, higher methylmercury levels tend to occur in predatory fish that are higher up in the food chain.   Among different individual animals of the same species, larger older fish tend to have higher methylmercury levels than those that are younger.  However, because wild-caught fish supplies are dwindling, the supply of high mercury fish is too.  Since the aquaculture fish that are replacing them are lower down in the food chain and are harvested when they are young, they tend to have uniformly low methylmercury levels.  However, they can have higher levels of other contaminants like antibiotics and dioxins.

In addition to mercury, fish can be an important source of many nutrients.  Besides protein, the most noted of these are omega-3 fatty acids.  There have many studies on potential nutritional effects of isolated omega-3 fatty acids (i.e. fish-oil capsules), and most of the results are negative.  Perhaps the best evidence comes from epidemiological studies of fish consumptions where modest levels of fish consumption appear to slightly reduce the incidence of stroke, cardiovascular disease, and perhaps other outcomes like neurobehavioral development (FDA, 2014).  So, omega-3 fatty acids, or possibly some other constituent in fish, probably do not correct a common nutritional deficiency, but it does appear that they may address  a nutritional deficiency that is only found in people who consume little or no fish.

A Survey of Fish Species Sold in the United States

The FDA has been collecting samples from the U.S. market since the 1990.  While early effects focused only on shark and swordfish, the current data base has over 60 categories of fish.  The table below shows estimated average methylmercury for 51 categories, which as of 2012 included over 99% of all species sold in the United States.  However, the FDA database hasn’t been updated since 2010, and the fish on the market are constantly changing, so this table is not exactly current.  But, it will have to do for now.

Also included in the table are omega-3 concentrations.  Most of these are taken from the USDA nutrient database.  While the FDA methylmercury concentrations are reported with ranges (and raw data if you like), the USDA only reports average values.  In order to emphasize the nutrient value of each category, they are sorted by the ratio omega-3 concentrations to methylmercury concentrations.  If you consume fish on a regular basis anyway, then the omega-3s are probably not really an issue, so you may be more interested in just methylmercury concentrations.  They are sorted that way on the FDA web summary and in the FDA risk-benefit report (FDA, 2014).

Fish Category	Hg (µg per g)	Total Ω-3 g/100g	µg Hg per g Ω-3
Sardines	0.02	1.19	1.7
Salmon	0.02	1.18	2.0
Oysters and Mussels	0.02	0.70	2.1
Anchovies, Herring, and Shad	0.05	2.02	2.5
Shrimp	0.01	0.35	3.1
Trout, Freshwater	0.03	0.93	3.4
Scallops	0.01	0.19	3.7
Mackerel, Atlantic and Atka	0.05	1.20	4.1
Mackerel, Chub	0.09	1.25	7.0
Pollock	0.04	0.53	7.0
Smelt	0.07	0.89	7.5
Catfish	0.02	0.22	7.6
Butterfish	0.06	0.73	8.0
Whitefish	0.10	0.91	11.0
Clams	0.02	0.20	11.6
Tilefish, Atlantic	0.11	0.91	12.2
Squid	0.07	0.54	12.9
Tilapia	0.01	0.09	14.3
Crabs	0.06	0.38	16.6
Sablefish	0.37	1.81	20.4
Crawfish	0.03	0.16	20.7
Lobsters, Spiny	0.11	0.48	22.9
Flatfish	0.08	0.30	25.3
Bass, Saltwater	0.25	0.97	25.9
Mackerel, Spanish	0.37	1.25	29.7
Halibut	0.22	0.71	31.4
Bluefish	0.35	0.99	35.4
Carp and Buffalofish	0.17	0.45	37.7
Croaker, Atlantic	0.08	0.20	38.6
Tuna, Albacore Canned, Water	0.35	0.86	40.6
Haddock, Hake, and Monkfish	0.07	0.16	41.9
Bass, Freshwater	0.32	0.76	41.9
Trout, Saltwater	0.26	0.62	42.0
Tuna, Light Canned, Water	0.12	0.27	44.4
Skate	0.14	0.30	45.7
Perch, Ocean and Mullet	0.16	0.32	49.4
Perch, Freshwater	0.15	0.29	50.9
Pike	0.14	0.27	52.3
Cod	0.09	0.16	55.6
Lobsters, American	0.11	0.20	56.4
Tuna, Fresh	0.39	0.65	59.9
Snapper, Porgy, and Sheepshead	0.16	0.26	62.6
Marlin	0.49	0.50	98.0
Croaker, Pacific	0.30	0.30	100.0
Lingcod and Scorpionfish	0.29	0.26	108.7
Swordfish	1.00	0.90	111.2
Shark	0.98	0.69	142.2
Tilefish, Gulf	1.45	0.80	181.3
Mackerel, King	0.73	0.40	182.0
Grouper	0.46	0.25	185.5
Orange Roughy	0.57	0.03	1838.7

Software

One of the problems with public health advice is that it often doesn’t take into account other things that individual consumers want.  Maybe you would rather eat more fish, or less.  Maybe you prefer tuna to salmon.  Maybe fish is too expensive.  So, instead of handing out advice I’m going to concentrate on giving out information.  Then you can figure out whether or not it’s worth changing your fish eating habits for yourself.  The first step is figuring out how your fish consumption choices affect how much methylmercury and omega-3 are in your diet.

Personal_Seafood_and_MeHg_Intake_Estimator.xls

References

Food and Agriculture Organization (2016).  Aquaculture Fact Sheets.

U.S. Food and Drug Administration (2014). Quantitative Assessment of the Net Effects on Fetal Neurodevelopment from Eating Commercial Fish (As Measured by IQ and also by Early Age Verbal Development in Children).  

Official Post Soundtrack

Murphy, Peter (1989).  Deep Ocean Vast Sea.  In: Deep, Track 1.

Post  Notes

Thesis Post #56.  The is the first of what I think will be a five part series that describes a individualized version of the risk-benefit model I created for the FDA [part two was the last post, so part three will be next].  I'm putting it out in parts largely to provide documentation of the model -- the code is all open.  In the end, I will combine them all into a single program.

Methylmercury in Blood and Hair

Why Blood and Hair Concentrations Matter

The best evidence for the toxicity of methylmercury to humans comes from poisoning epidemics in Japan and Iraq.  However, in both those epidemics, the exact amount of methylmercury consumed by the people who were poisoned was unknown.  In Japan, by the time methylmercury was established as the cause of the disease, it was too late to figure out, at least on an individual basis, what the amount of methylmercury ingested was.  However, in Iraq measurements of mercury in blood and hair were taken in order to gauge how much people were exposed to afterward.  That can be done because mercury is slowly (months) removed from the blood, and mercury in hair can stay there for years.  Similarly, blood and or hair measurements have been used in epidemiology studies involving populations that consume large amounts of fish to gauge the extent of exposure of different individuals to methylmercury.

Predicting Blood MethylMercury Based On Dietary Exposure

Biomarkers are useful for characterizing the relationship between exposure and the toxic effects, but since most exposure to methylmercury is usually from fish, it leaves a question hanging:  What is the relationship between consuming fish on a regular basis and levels of methylmercury in blood and hair?  Since this is a very important issue, a study with four different controlled doses of methylmercury from fish in twenty human subjects over a ninety day period (Sherlock et al, 1984).  This study was conducted in the UK over thirty years ago, and because of current restrictions on the use of human subjects probably couldn’t be done today.  Since the change in blood concentrations relative appears to be linear (i.e. has the same proportion regardless of dose), the following analysis assumes linear in order to focus on two other issues, namely the impact of body weight and other unattributed sources of variation.

While recommended dosages of drugs are often prescribed without consideration of body weight, toxicologists usually presume that the internal dose (i.e the concentration in blood) will be directly proportion to body weight.  But contrary to either of those traditional approaches, Sherlock et al (1984) suggested that a correction factor of body weight to the one-third power is the most appropriate.  Since individual subject data were published in the paper, we can look for ourselves. 

The grey squares in the graph above show the uncorrected data from all 20 subjects.  There is clearly a correlation in the relationship between incremental methylmercury levels and body, indicating that some correction for body weight is necessary.  However, correcting the values by assuming proportionality (the black triangles) seems to overcorrect since it results in a trend going the other way.  The correction suggested by Sherlock et al, 1984 of body weight to the one-third power (black diamonds) does work well.  The best correction factor of all seems to of body weight to the power 0.44 (open squares); since the black regression line is completely flat, it corrects for the influence of body weight as well as possible.

However, there is still a considerable amount of variation that is not accounted for.  Using several alternative statistical distributions to describe the additional variation found with corrected values for a 70 kg person yields the following:

Predicting Hair MethylMercury Based On Blood Concentrations

Since most studies use hair as a biomarker, it is also necessary to relate hair methylmercury to dietary exposure from fish.  The a chronic study used n Sherlock et al (1984), also measured hair values (reported in Hislop et al. (1983), but only for the data from are the most relevant to a chronic exposure assessment.  However, hair values were only measured for five of the 20 subjects in the study, all of whom were male.  In addition, only the ranges for the hair-blood ratios are reported.  Other studies have more individual data points and are therefore potentially more useful at characterizing the full range of pharmacokinetic variability.  However, there are a number of other problems with these data. First, blood measurements fluctuate and are dependent on the time since the last fish meal, and as a result, measurements made at a single point in time may not accurately reflect long-term exposure.  Second, since inorganic mercury was not measured independently in hair, it is also possible that there is some contamination of hair from inorganic mercury – perhaps from environmental sources.  Third, errors in the chemical analysis are more likely to be substantial at lower concentrations in blood or hair (i.e. near the limit of detection), resulting in either unrealistically high or low ratios.  Regardless of the explanation, actual pharmacokinetic variation in the studies reporting single measurements of blood and hair is almost certainly narrower that the apparent distribution. 

The following figure shows summary data using a lognormal distribution to represent population variability with uncertainty distributions for the parameters.  The values were chosen to be centered on the values from Hislop, but to also encompass some of the variation from the other studies as well.

Software

Combining the results of the preceding analysis allows prediction of blood and hair levels, albeit with more than a little uncertainty.  Although the underlying functions are statistical descriptions of what happens in a population, they can also be used to predict what will happen in an individual if the population variability is treated as an additional uncertainty.  In that vein, a simple simulation for estimating personal concentrations for methylmercury in blood and hair is presented below.  It also includes a distribution intended to represent other exposures to methylmercury that is based on results from a survey of blood values in the U.S. (EPA, 2013).

The simulation is written in Microsoft Excel and has VBA macros, so macros need to be enabled and you are going to have to trust me as a source.  Sorry.

MeHg_Hair_and_Blood_Simulation.xls

References

Budtz-Jørgensen, E., Grandjean, P., Jorgensen, P.J., Weihe, P., Keiding, N. (2004).  Association between mercury concentrations in blood and hair in methylmercury-exposed subjects at different ages.  Environmental Research, 95, 385-393.

Centers for Disease Control and Prevention. (2005). National Center for Health Statistics, National Health and Nutrition Examination Survey, 2003-2004 data files.  There are more recent values, but they haven’t changed very much.

Hislop, J.S., Collier, T.R., White, G.F., Khathing, D.T., French, E. (1983).  The Use of Keratinised Tissues to Monitor the Detailed Exposure of Man to Methyl Mercury from Fish.  Chemical Toxicology and Clinical Chemistry of Metals, edited by Brown, S.S. and Savory, J.  Academic Press, New York, 145-148.

Sherlock, J., Hislop, D., Newton, G., Topping, G., Whittle, K. (1984).  Elevation of mercury in human blood from controlled ingestion of methylmercury in fish.  Human Toxicology 3:117-131.

U.S. Environmental Protection Agency (2013).  Trends in Blood Mercury Concentrations and Fish Consumption Among U.S. Women of Childbearing Age NHANES, 1999-2010.  Final Report July 2013 EPA-823-R-13-002.   

U.S. Food and Drug Administration (2014). Quantitative Assessment of the Net Effects on Fetal Neurodevelopment from Eating Commercial Fish (As Measured by IQ and also by Early Age Verbal Development in Children).   Additional technical details of the analyses described above can be found in Appendix C, section (a)(3). 

Software

A simple simulation for estimating personal concentrations for methylmercury in blood and hair.  It has VBA macros, so they need to be enabled and you are going to have to trust me as a source.  Sorry.

MeHg_Hair_and_Blood_Simulation.xls

Official Post Soundtrack

Supertramp (1974).  Bloody Well Right.  In: Crime of the Century, Track 2.

Post Notes

Thesis Post #55.  This is the first one with quantitative analysis, which is from the FDA fish risk benefit report.  I tried to make the explanations less technical, but I suppose that my success in that regard is pretty marginal.  l plan several on more, which will in the end develop into a personal risk assessment model that will deviate somewhat from what is in the report.  What is posted here just covers methylmercury pharmacokinetics.  A personal fish consumption module and dose-response functions for both mercury risks and fish benefits will be added later.  Lame live soundtrack is the best I could do.

Data Economics

In their recent seminal work, Longo and Drazo (2016) sketched out what might be called the trickle-down theory of data economics.  But, to really get off the ground, this fledging field needs some alternative theories.  Towards that end, a brief snapshot of the original theory and two alternatives are presented forthwith.

Haves vs Have-Nots

The Longo and Drazo theory posits that data is fundamentally the property of “front-line researchers” who created the data, and therefore, are the rightful owners of the data.   On the other hand, you have a new lower class of researchers that make no data whatsoever.  Many of these computer-toting “research parasites” probably never got a research grant in their life, never did an experiment, yet they somehow think they are entitled to data just because they don’t have any.  Slackers.

But, the data hosts can be magnanimous on occasion.  If it suits their interests, they may be willing to let the research parasites feed at their data trough by working “symbiotically”.  However, if the parasites are pushing a theory that doesn’t interest them, or even worse, runs counter to their own interpretation, forget about it.  And if the hosts are dead, well, the parasites are just going to have to go hungry.

Farmers vs Hunter-Gatherers

In this theory, the data makers are akin to farmers.  They toil in the fields near the Ivory Tower in which they live.   These farmers depend on the data they grow for sustenance.  But they often don’t consume the whole crop, and often leave much of it out in the field to rot. Out beyond the fields, there are a roaming class of hunter-gatherers.  These researchers are often living hand-to-mouth, just trying to get whatever data they can find that will help them solve the problem they happen to be working on that day.  Even though they do have their own data that they have gleaned from personal experience, as you may imagine, they often want to take it from the data farmers.  Scavengers from neighboring fiefdoms may also wander over to snatch data from the farmers too.

If the farmers really need the data for themselves, then of course they will object to having the data they created snatched from them.  On the other hand, if they have already gotten what they need, why not just let the gatherers have it?

Polluters vs Regulators

Industrialized countries are churning out data and releasing it into the intellectual environment at an ever increasing rate.  Unfortunately, instead of being released in pure form, the data are often contaminated with byproducts known as theories.  While these theories are often innocuous or even beneficial, many theories are deleterious to the mental health of anyone exposed to them.  The use of the log(dose) transform, for instance.

 

So, there obviously needs to be a public mechanism for mitigating the release of noxious theories into the environment.  The government could perhaps establish an academy to sort through epistemological disputes.  Oh wait, that already happened.  But, what if the academy itself is contaminated with bad theories?  Maybe there needs to be an open process for evaluating whether not the data really justify the theories they are issued with.  Hard to see how that can happen without making the data available unsullied.

Reference

Longo DL and Drazen JM (2016).  Data Sharing.  N Engl J Med 374:276-277

86 Billion Neurons, More or Less

A Few Basic Facts

A normal human brain has approximately 86 billion neurons, which is a lot even by mammalian standards.  What makes neurons special is that they are all interconnected by axons and synapses that let neurons send and receive signals to other neurons quickly.  Signals along the neuron and axon are transmitted by electrical impulses that are enabled by ion channels that briefly let charged ions cross the membrane of the cell.  Synapses connect axon terminals to dendrites in other neurons by molecules, called neurotransmitters, that are released from axon terminals and interact with receptors on connected dendrites.  Although the number of synapses each neuron has varies tremendously, the average number is estimated to be over a thousand, and the total number in the brain is estimated to be over 100 trillion (that’s 100,000,000,000,000). 

Not all neurons are the same in structure or function.  Some are closely associated with sensory systems (e.g. eyes and ears), some with motivational systems (e.g. thirst, hunger, fear, and sex), while still others are involved in controlling muscle activity, and then there are neurons that are connected with everything in general and nothing in particular.  While most neurons have short axons, some have long axons that connect to other neurons, muscles, and senses that are far away.  For example, there are neurons in the spinal cord that have axons that run the length of both arms and legs. 

Not all synapses are alike either.  Some are excitatory, meaning they stimulate the neurons they are attached to send a signal.  Others are inhibitory, meaning they act to prevent another neuron from sending a signal.  The neurotransmitters used at different synapses also vary.  While there are 10 different main neurotransmitters, there are many other minor transmitters as well.

Unlike most other cells in the body, most neurons are formed either before birth or shortly afterward.  It’s all downhill after that – the number of neurons decreases to at least some extent with age.  On the other hand, synapses some and go.  Although many synapses are formed when the brain is first developed, the formation of new synapses throughout life is what makes learning and memory possible.

Disrupting Brain Function

There are many ways different substances can alter or impair brain function.  The most common and well known mechanism is to either mimic or block the actions of neurotransmitters.  Caffeine acts that way, and so do many legal and illegal drugs.  Alcohol probably acts by generally impairing axonal transmission in all neurons.  Even though the actions of many neuroactive chemicals are temporary, an addiction can develop with prolonged use.  That happens because the brain adapts to having more or less of a particular transmitter, which means the brain will then function abnormally without the drug.  Short term effects on neurons can also be fatal.  For example, many pesticides act by preventing the deactivation of the neurotransmitter (acetylcholine) responsible for neuronal activation of muscles, including those responsible for breathing. 

But, some chemicals also have long term effects.  Alcohol can cause neuronal cell death, which is irreversible.  Other toxic chemicals can cause axons to degenerate, which may not grow back.  But, perhaps the worst thing a toxic chemical can do is to prevent the brain from developing in the first place.  That can happen when a substance either interferes with neuronal growth before or just after birth, or with the development of synapses before birth or later in life.  Methylmercury and lead are both examples of developmental neurotoxicants.  Methylmercury is thought to act primarily before birth, while lead exposure is thought to be most detrimental in young children.  However, the exact mechanism responsible for the effects of either lead or mercury is largely unknown.

Biochemical Neurotoxicology

There are bazillions of toxic molecules in the body.  Let’s take methylmercury for instance. The average methylmercury blood concentrations in the United States is about 1.3 µg/liter and the blood volume of a pregnant woman (and fetus) is about 4 liters.  So, an average pregnant women has about 5 µg of methylmercury in her blood.  Since the molecular weight of methylmercury is 231 there are Avogadros number (6.2 x 10²³) of methyl mercury molecules in 231 g, and 9.4 x 10¹² molecules in the blood of average an average pregnant woman in the U.S.   There’s also mercury in other tissues, including the brain, so let’s just round to an even bazillion.  The main point here is that there are a lot – even more than the number of neurons and about the same as the number synapses.

So, what happens if a molecule of methylmercury gets into the blood?  Usually, nothing.  It hangs around for a few months and then gets eliminated.  But some of it crosses the placenta and goes into the fetus.  But, even there nothing usually happens.  It may go back out again, or it may go into other tissues like muscle where as far as anyone knows it isn’t toxic.  But some it gets into the brain of the fetus.  But even there, most of it floats around inside or outside the neurons and does nothing.  But, on some rare occasions, the molecule of methylmercury will bind to something like an ion channel or a protein necessary for synaptic development, and sometimes that may keep the neuron or synapse from developing as it normally would.  But even that's not necessarily so bad.   One neuron or one synapse among billions or trillions isn’t going to be missed.  On the other hand, one molecule isn’t the problem.  A bazillion molecules may not really be much of an issue either.  But a bazillion here, a bazillion there, and pretty soon you are talking about a real problem where brain function is reduced to a noticeable extent.

Thresholds

Toxicologists don’t ever prove there is absolutely no effect – they can only show that if there is an effect it isn’t big enough to be detectable.  Yet, they often suggest that somehow they know that there is some dose of a toxic substance that does absolutely nothing, which is called a threshold (e.g. Barnes and Dourson, 1988).  There is no evidence for it, so the threshold theory is pretty much just a fairy tale that is often repeated because people like to hear it.  It is true that for a number of reasons, high level exposures can be much worse than low level exposures (e.g. cooperative binding, saturable metabolism), but that’s not really the same thing as a threshold: If several bazillion molecules have a noticeable effect, a bazillion or fewer probably do damage as well, only less.  In toxicology, less is better than more, so that’s good.  But if you would like zero, well you can’t have it.  Anyone who says otherwise is either lying or sadly mistaken.

In any case, the EPA has adopted the position that there is no threshold for the effects of lead.  In fact, that is given as a reason for not having a Reference Dose for lead (EPA, 2004).  On the other hand, the EPA supposes that there is a threshold for methylmercury and gives that as a reason for having a Reference Dose (EPA, 2001).  I think the EPA has it right for lead and wrong for methylmercury.  At least that’s the way my synapses have it sorted out.

References

Barnes DG and Dourson ML (1988).  Reference Dose (RfD): Description and Use in Health Risk Assessments.  Regul Pharmacol Toxicol 8:471-486.  Also at http://www.epa.gov/IRIS/rfd.htm

Environmental Protection Agency (2001).  Methylmercury (MeHg); CASRN 22967-92-6

Environmental Protection Agency (2004).  Lead and compounds (inorganic); CASRN 7439-92-1

Official Post Soundtrack

Pink Floyd (1973).  Brain Damage.  In: Dark Side of the Moon, Track 9.

Post Notes

Thesis Post #54.  This is a part of the semi-lay toxicology series that i began last spring but have done nothing with since.   I'm thinking a majority of by near future posts will be of this ilk, but we'll see. Besides providing a basic neuroscience overview, I am obviously taking on the threshold issue that still! has it hooks into the public and regulatory psyche.  Dumb, dumb, dumb.