Tuesday, January 05, 2010

Random acts of ill-health   posted by Razib @ 1/05/2010 01:49:00 PM

Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease:
Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.

Why you? Because.


Sunday, December 20, 2009

Coincidence or adaptation?   posted by Razib @ 12/20/2009 01:48:00 AM

Different Evolutionary Histories of the Coagulation Factor VII Gene in Human Populations?:
Immoderate blood clotting constitutes a risk factor for cardiovascular disease in modern industrialised societies, but is believed to have conferred a survival advantage, i.e. faster recovery from bleeding, on our ancestors. Here, we investigate the evolutionary history of the Coagulation Factor VII gene (F7) by analysing five cardiovascular-risk-associated mutations from the F7 promoter and nine neutral polymorphisms (six SNPs and three microsatellites) from the flanking region in 16 populations from the broader Mediterranean region, South Saharan Africa and Bolivia (687 individuals in total). Population differentiation and selection tests were performed and linkage disequilibrium patterns were investigated. In all samples, no linkage disequilibrium between adjacent F7 promoter mutations −402 and −401 was observed. No selection signals were detected in any of the samples from the broader Mediterranean region and South Saharan Africa, while some of the data suggested a potential signal of positive selection for the F7 promoter in the Native American samples from Bolivia. In conclusion, our data suggest, although do not prove, different evolutionary histories in the F7 promoter region between Mediterraneans and Amerindians.

The primary aim of this research seems to have been to figure out if the variance in a medical trait (prevalence in cardiovascular disease) could be traced to variance in this coagulation factor gene. Doesn't seem like that panned out. But their "Native American" sample happened to consist of Bolivian highlanders, Quechua and Aymara speakers. There are long haplotypes amongst these populations for the variant which seems result in increased risk for cardiovascular disease. I don't know much about physiology, but I immediately wondered if modulating traits which effect hematological system might have nasty side-effects. The populations of the Andes of course have developed some genetic tricks to optimize their functioning at high altitudes, bt tricks often have trade-offs. Of course this doesn't necessarily mean it's selection which drove up the frequency of the variant in question. Native populations of the New World seem to have gone through a population bottleneck, which can generate some of the same patterns. But there are enough non-highland groups whereby one could check to see if they have the high risk variant and a long haplotype as well.

Labels: ,

Friday, November 27, 2009

Where the fat folks live   posted by Razib @ 11/27/2009 12:44:00 AM

Since it's after Thanksgiving and I'm feeling bloated, I figure a follow up to the post on obesity and diabetes might be apropos. I want to focus on obesity. I have the raw county-by-county data, but obviously it isn't broken down by race. But, I do have the proportions for reach race by county, and, the CDC provides state-by-state breakdowns of the proportion of obese by race. So I decided to "estimate" the proportion of whites obese by county.

1) By "white," I mean "Non-Hispanic white." I'm going to say "white" from now on exclusive of Hispanics.

2) Some states, such as Vermont, do not have a large enough sample to estimate the obesity proportion of blacks. I just used a neighboring state to fill in the numbers. This guesstimate is really not much of an issue because the proportion of blacks is so low in the states I had to estimate that the estimate of obesity for whites and estimate of obesity for all races is the same in these counties anyhow.

3) Simple algebra. Total Obesity Percent In County = (Obesity Percent Whites) X (Percent Whites) + (Obesity Percent Blacks) X (Percent Blacks) + (Obesity Percent Latinos) X (Percent Latinos)

For the obesity percent of blacks and Latinos I only have state level data, so this is going to be a rough estimate. And it's going to result in the variation exhibiting state-to-state discontinuities, since the county variable is dependent on a state level variable. Also, I discarded some counties where the usage of state level data caused really big distortions. Along the Mexican border Latinos are not nearly as obese as they are further into the United States, so I end up with numbers where whites have negative obesity percentages to make the math work out. These are counties which are 90% or more Latino with relatively low obesity numbers.

I did the map shading the way I normally do. Blue is above the median value, and red below the median value, with the scale being set to their max and mins respectively. Unfortunately this causes a problem in the scaling in terms of an asymmetry because one side of the distribution will tend to have a more extreme outlier (usually the above median is where the skew is).

Here's the map with all the populations:

This is basically the earlier map except shaded differently. Here are the summary statistics for obesity by county:

min = 12.40
1st quartile = 26.60
median = 28.40
mean = 28.25
3rd quartile = 30.20
max = 43.70

Now for my estimate of whites only:

As you can see, the use of state level is causing some distortions. Also, you see something peculiar in the summary statistics:

1st quartile = 25.54
median = 27.62
mean = 26.71
3rd quartile = 29.47
max = 58.11

These averages don't align with the CDC values aggregated. But that's because I'm looking at county level data, and not weighting by population. Lots of low density counties with few people have many obese people. Instead of looking at national averages, we're looking at regional variations.

On the estimates, Texas probably jumps out at you. To my surprise it turns out that whites in Texas are a touch lighter than the national average for whites! For me the big thing that sticks out is that Appalachia seems to be split in two, along the Appalachian Trail (I feel funny mentioning the Appalachian Trail....). Some areas, such as New England, Colorado and California do not surprise in terms of whites who are below the national median. But again there is a pattern of some pockets in the Upper Midwest being relatively under the norm in the proportion of obesity. Some of you might be surprised by the Pacific Northwest, but this region is characterized by urban-rural polarization.

What are the correlations by ethnicity? Here are the correlations with white obesity in terms of ancestral proportion (the proportion of ethnicity X as a proportion of whites):

English = -0.17
German = -0.02
American = 0.07
Scots Irish = -0.13
Irish = -0.19

These are very modest correlations. Probably mostly explained by geography. How about voting?

Obama vote = -0.21

Again, modest. Median Family Income? Only -0.14! That surprised me. Interestingly, Median Home Value had a -0.26 correlation with obesity. Of course the "Dirt Gap" tracks this; in places where people are thinner property values are higher, and rose higher in the past decade. The proportion who have a college degree is like home value, a correlation of -0.25.

None of this is really surprising, on the aggregate level you know that wealthier and more educated people are thinner. So I might as well do something that's not totally predictable. Most of the variance of obesity on the county level isn't predicated by educational levels, but a non-trivial fraction is. I decided to fit a loess curve to the plot of obesity (white) who are college educated. Then I simply took the residuals above and below the line and shaded them blue and red respectively. In other words, blue areas have a lot of fat people for the number of college graduates, while red areas have relatively few fat people for the number of college graduates.

Labels: , ,

Wednesday, September 16, 2009

Did iatrogenic harm select for supernatural beliefs?   posted by agnostic @ 9/16/2009 08:10:00 PM

Toward the end of this episode of EconTalk, Nassim Taleb (Fooled by Randomness, The Black Swan) talks about religion and the history of medicine. He notes that one of the benefits of adhering to religious practices was that you probably avoided going to a doctor when you were in trouble -- you prayed to a god or whatever other supernatural entity your religion said would help you out. Why was this a benefit? Because before roughly 50 to 100 years ago, going to the doctor was worse than doing nothing. He bled you, gave your wife a disease by not washing his hands while delivering her baby, etc.

Basically, before very recent times, doctors were parasites. They did not specialize in healing you, but in conning you into thinking that they could heal you -- for a small fee -- all while making you worse, on average. This makes me think: there would have been a selection pressure on human beings to be skeptical of materialist claims about the world -- or at least about the nature of ourselves -- and thus, by default, to be naturally inclined toward supernatural beliefs. Of course, praying to Zeus might not have done an awful lot of good -- but at least it wouldn't have given you new infections like a hospital would, and at least it wouldn't have bled you dry. (And there may have been some benefit from all the social interactions that you got by attending religious services regularly vs. being socially isolated.)

Natural selection operates on the tiniest differences in relative fitness, and for most of human existence there must have been more than a little difference in fitness between those who eagerly sought out the help of a medicine man / doctor and those who just went to church (or wherever) and prayed to the spirits instead. This may be an original hypothesis, but I don't claim so since I haven't read much on the various theories of why religion is part of human nature. Taleb came pretty close to saying so, but not explicitly. Most economists talk about what's rational or utility-maximizing, without making that final link to evolutionary fitness. To its credit, the idea has a pretty solid basis for the necessary differences in relative fitness between believers and non-believers.

Labels: , , ,

Monday, August 31, 2009

Recession = less death?   posted by Razib @ 8/31/2009 09:33:00 PM

The effect of economic recession on population health:
Economic recessions have paradoxical effects on the mortality trends of populations in rich countries. Contrary to what might have been expected, economic downturns during the 20th century were associated with declines in mortality rates. In terms of business cycles, mortality is procyclical, meaning it goes up with economic expansions and down with contractions, and not countercyclical (the opposite), as expected. So while most nations enjoyed sustained declines in mortality during the last century, the pace of the decline has been slower during economic booms and greater during so-called busts. The first rigorous studies demonstrating this trend have appeared only in the past 9 years, although the concept is not new. In contrast, for poor countries, shared economic growth appears to improve health by providing the means to meet essential needs such as food, clean water and shelter, as well access to basic health care services. But after a country reaches $5000 to $10 000 gross national product (GNP) per capita (or gross domestic product or gross national income per capita, all of which are similar for our purposes here), few health benefits arise from further economic growth...Health trends in Sweden illustrate this effect.

Greg Cochran told me about this phenomenon in regards to the Great Depression last year.

Labels: ,

Tuesday, May 19, 2009

Eczema & asthma   posted by Razib @ 5/19/2009 12:18:00 PM

Skin-Derived TSLP Triggers Progression from Epidermal-Barrier Defects to Asthma:
Eczema (atopic dermatitis) is a common allergic skin inflammation that has a particularly high prevalence among children. Importantly, a large proportion of people suffering from eczema go on to develop asthma later in life. Although the susceptibility of eczema patients to asthma is well documented, the mechanism that mediates "atopic march"- the progression from eczema to asthma - is unclear. We used genetic engineering to generate mice with chronic skin-barrier defects and a subsequent eczema-like disorder. With these mice, we were able to investigate how skin-specific defects predisposed the lungs to allergic asthma. We identified thymic stromal lymphopoietin (TSLP), a cytokine that is secreted by barrier-defective skin into the systemic circulation, as the agent sensitizing the lung to allergens. We demonstrated that high systemic levels of skin-derived TSLP were both required and sufficient to render lung airways hypersensitive to allergens. Thus, these data suggest that early treatment of skin-barrier defects to prevent TSLP overexpression, and systemic inhibition of TSLP, may be crucial in preventing the progression from eczema to asthma.

Labels: ,

Tuesday, September 25, 2007

Infectious disease, how bad does it do a body?   posted by Razib @ 9/25/2007 11:54:00 PM

In my post below I respond to Bryan Caplan's critique of Greg Clark's claim that disease can increase per capita income because it reduces population (i.e., same population has a bigger resource base to work with).1 I go the route of the two handed economist by suggesting that whether Clark or Caplan is right depends on the details.2 Herrick adds in the comments:
Caplan's big claim is that almost anything that persistently raises death rates is likely to persistently reduce output per living worker. It that true?

One possible source of persistent increases in death rates that have no impact on productivity: Many kinds of infectious disease.

I'd welcome medically-informed comments on the topic, but it seems possible for infectious disease (from, say the bad sanitation that Clark emphasizes) to raise the chance of dying any given month without appreciably hurting your productivity most of the time.

Scenario: You get sick for a week or two every couple of years, and if you survive, you go back to being productive. If you don't survive, well then, you're pushing up the death rate.

As I suggest below I think that Caplan is wrong if he wants to claim that productivity is always decreased in direct proportion to the increased disease load (ergo, death rate) of a population. This would prevent the rise in incomes which Clark predicts as the lower productivity of each individual means that the same amount of land can support fewer people at or above subsistence. In A Farewell to Alms Clark reports a rise in incomes after the Black Death, and, amongst native peoples in the New World after Old World diseases ravaged them. Obviously this is one extreme cause: a highly lethal infectious disease which cuts down a large proportion of the population very quickly, and then recedes. The other scenario is a case where there is an endemic infection which reduces physiological fitness across the whole population, reducing lifespan and increasing death rates, but also dampening economic productivity. Then there are cases where there is a wide variance within the population in regards to susceptibility toward infectious agents. This might be more like the first scenario, a large number of people die very quickly, while many others are spared because of some immunity. And so on.

From Darwinian first principles it seems that there should be a large number of pathogens which are infectious but not fatal. Though reducing physiological fitness, they don't knock out their host because to do so would result in their own reduced evolutionary fitness. But hey, Herrick asked for expert opinion. I was actually hoping that someone with medical expertise (e.g., tropical diseases?) would weigh in on that thread, but that didn't happen. So I come to you with open hands and ask you to enlighten....

Update: Greg Clark responds directly to the Caplan critique. As a non-economist I'm more interested in what the empirical historical data says, and what little I know seems to agree with the general thrust of Clark's point.

1 - That sentence should filter out chimpanzee readers since it should be totally incomprehensible to them.

2 - No shit it depends on the details!


Thursday, July 05, 2007

A top-down approach to genetic networks   posted by p-ter @ 7/05/2007 08:08:00 PM

One of the interesting findings to come from the recent burst of genome-wide association studies is that many seemingly disparate phenotypes share some genetic pathways. I don't think many people would have a priori considered the possibility of a genetic link between prostate cancer and type II diabetes, yet that's what the data suggest. Other links are somewhat more predictable-- type I diabetes and Crohn's disease both have an autoimmune component, so a genetic link might have been expected. And cornary heart disease and type II diabetes share some envronmental risk factors, so perhaps it's to be expected that similar genetic networks play a role in the two.

These genetic links have all been uncovered by classic reductionist methods-- find the molecular variation that predisposes to disease 1, find the molecular variation that predisposes to disease 2, and compare the two sets. It's simple, and it works.

However, a clever new paper takes a different approach:
Geneticists and epidemiologists often observe that certain hereditary disorders cooccur in individual patients significantly more (or significantly less) frequently than expected, suggesting there is a genetic variation that predisposes its bearer to multiple disorders, or that protects against some disorders while predisposing to others. We suggest that, by using a large number of phenotypic observations about multiple disorders and an appropriate statistical model, we can infer genetic overlaps between phenotypes. Our proof-of-concept analysis of 1.5 million patient records and 161 disorders indicates that disease phenotypes form a highly connected network of strong pairwise correlations. Our modeling approach, under appropriate assumptions, allows us to estimate from these correlations the size of putative genetic overlaps.
This is data mining at its finest.

I'll admit I didn't go through all of the hundreds of pages of supplementary material, but this is fascinating stuff. The authors seem to be particularly interested in autism, which they find correlates with a number of neurological disorders, but also bacterial and viral infections and autoimmune disease:
Our estimated significant overlap between autism and tuberculosis may indicate that both diseases are associated with genetic changes weakening the immune system
Or consider the overlap between bipolar disorder and breast cancer:
Although the competitive genetic overlap between bipolar disorder and female breast cancer has not been reported, there is recent indirect evidence that supports it: a well-established breast cancer drug, tamoxifen, was recently discovered to be effective in treating symptoms of bipolar disorder.
The amount of data generated by the medical community each day is staggering, and as genetic information gets cheaper, it will increasingly be a part of that data. Half the game is knowing what to look for.

Labels: ,

Wednesday, May 16, 2007

Genetics of obesity   posted by p-ter @ 5/16/2007 02:45:00 PM

I realize I'm sort of beating a dead horse by reporting every single high-profile genome-wide association scan (for example), but it's worth pointing out their successes, as there was serious opposition to the HapMap project that laid the groundwork for these studies. So in that spirit, I'll point out this paper, which identifies a common variant in the FTO gene as being associated with obesity:
An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.
One of the most important points about genome-wide association studies is that they're (more or less) unbiased-- that is, you don't have to think about which genes could be involved in the phenotype before studying it. Some people consider this a liability, some a blessing. I'm in the latter group, as a strong signal in a genome-wide association can in some cases lead to new candidate genes, new hypotheses and expose interesting biology. This is precisely one of those cases. Here's what's known about the gene identified in this study:
FTO is a gene of unknown function in an unknown pathway that was originally cloned as a result of the identification of a fused-toe (Ft) mutant mouse that results from a 1.6-Mb deletion of mouse chromosome 8. Three genes of unknown function (Fts, Ftm and Fto), along with three members of the Iroquois gene family (Irx3, Irx5, and Irx6 from the IrxB gene cluster), are deleted in Ft mice. The homozygous Ft mouse is embryonically lethal and shows abnormal development, including left/right asymmetry. Heterozygous animals survive and are characterized by fused toes on the forelimbs and thymic hyperplasia but have not been reported to have altered body weight or adiposity. The fused-toe mutant is a poor model for studying the role of altered Fto activity, because multiple genes are deleted. Neither isolated inactivation nor overexpression of Fto has been described.
So essentially, nothing is known about this gene. Thanks to this study, this is unlikely to be the case for long.

Labels: ,

Friday, May 04, 2007

Treatments for some Mendelian diseases in the works?   posted by p-ter @ 5/04/2007 09:58:00 AM

One of the most consistent complaints about medical genetics research is that it's great at finding the gene/genes underlying a disease, but finding the gene/genes doesn't necessarily lead to any sort of treatment. The genes for cystic fibrosis and Duchenne muscular dystrophy, for example, were both identified in the late '80s. Both remain uncured. In fact, the genes underlying a large number of so-called "Mendelian" diseases (named because they are essentually due to defects in a single gene, unlike "complex" or "multifactorial" diseases) were identified in a mad rush after the realization in 1980 that disease genes could be found without knowing anything a priori about a disease or its genetics. As far as I know, no treatments have come out of these studies.

But as they say, Rome was not built in a day. If the precise genetic defect underlying a disease can be indentified, someone will find a way to fix it, though it may take many years, new technologies, and a lot of luck. So it's heartening to see a report in this week's Nature on the identification of a compound that may one day be a treatment for disorders caused by nonsense mutations (mutations that cause a truncated protein). From the abstract:
Nonsense mutations promote premature translational termination and cause anywhere from 5-70% of the individual cases of most inherited diseases. Studies on nonsense-mediated cystic fibrosis have indicated that boosting specific protein synthesis from <1% to as little as 5% of normal levels may greatly reduce the severity or eliminate the principal manifestations of disease. To address the need for a drug capable of suppressing premature termination, we identified PTC124-a new chemical entity that selectively induces ribosomal readthrough of premature but not normal termination codons.
The selectivity of PTC124 for premature termination codons, its well characterized activity profile, oral bioavailability and pharmacological properties indicate that this drug may have broad clinical potential for the treatment of a large group of genetic disorders with limited or no therapeutic options.
Clinical trials have apparently been initiated; this is a story to watch.

Labels: ,