Razib Khan One-stop-shopping for all of my content

June 14, 2017

The fad for dietary adaptations is not going away

Filed under: Diet,FADS,Genetics,Human Genetics — Razib Khan @ 7:21 pm

Food is a big deal for humans. Without it we die. Unlike some animals (here’s looking at you pandas) we’re omnivorous. We eat fruit, nuts, greens, meat, fish, and even fungus. Some of us even eat things which give off signals of being dangerous or unpalatable, whether it be hot sauce or lutefisk.

This ability to eat a wide variety of items is a human talent. Those who have put their cats on vegetarian diets know this. After a million or so years of being hunters and gatherers with a presumably varied diet for thousands and thousands of years most humans at any given time ate some form of grain based gruel. Though I am sympathetic to the argument that in terms of quality of life this was a detriment to median human well being, agriculture allowed our species to extract orders of magnitude more calories from a unit of land, though there were exceptions, such as in marine environments (more on this later).

Ergo, some scholars, most prominently Peter Bellwood, have argued that farming did not spread through cultural diffusion. Rather, farmers simply reproduced at much higher rates because of the efficiency of their lifestyle in comparison to that of hunter-gatherers. The latest research, using ancient DNA, broadly confirms this hypothesis. More precisely, it seems that cultural revolutions in the Holocene have shaped most of the genetic variation we see around us.

But genetic variation is not just a matter of genealogy. That is, the pattern of relationships, ancestor to descendent, and the extent of admixtures across lineages. Selection is also another parameter in evolutionary genetics. This can even have genome-wide impacts. It seems quite possible that current levels of Neanderthal ancestry are lower than might otherwise have been the case due to selection against functional variants derived from Neanderthals, which are less fitness against a modern human genetic background.

The importance of selection has long been known and explored. Sickle-cell anemia only exists because of balancing selection. Ancient DNA has revealed that many of the salient traits we associate with a given population, e.g., lactose tolerance or blue eyes, have undergone massive changes in population wide frequency over the last 10,000 years. Some of this is due to population replacement or admixture. But some of it is due to selection after the demographic events. To give a concrete example, the frequency of variants associated with blue eyes in modern Europeans dropped rapidly with the expansion of farmers from the Near East ~10,000 years ago, but has gradually increased over time until it is the modal allele in much of Northern Europe. Lactase persistence in contrast is not an ancient characteristic which has had its ups and downs, but something new that evolved due to the cultural shock of the adoption of dairy consumption by humans as adults. The region around lactase is one of the strongest signals of natural selection in the European genome, and ancient DNA confirms that the ubiquity of the lactase persistent allele is a very recent phenomenon.

But obviously lactase is not going to be the only target of selection in the human genome. Not only can humans eat many different things, but we change our portfolio of proportions rather quickly. In a Farewell to Alms the economic historian Gregory Clark observed that English peasants ate very differently before and after the Black Death. As any ecologist knows populations are resource constrained when they are near the carrying capacity, and England during the High Medieval period there was massive population growth due to gains in productivity (e.g., the moldboard plough) as well as intensification of farming and utilization of all the marginal land.

After the Black Death (which came in waves repeatedly) there was a massive population decline across much of Europe. Because institutions and practices were optimized toward maintaining a much higher population, European peasants lived a much better lifestyle after the population crash because the pie was being cut into far fewer pieces. In other words, centuries of life on the margins just scraping by did not mean that English peasants couldn’t live large when the times allowed for it. We were somewhat pre-adapted.

Our ability to eat a variety of items, and the constant varying of the proportions and kind of elements which go into our diet, mean that sciences like nutrition are very difficult. And, it also means that attempts to construct simple stories of adaptation and functional patterns from regions of the genome implicated in diet often fail. But with better analytic technologies (whole genome sequencing, large sample sizes) and some elbow grease some scientists are starting to get a better understanding.

A group of researchers at Cornell has been taking a closer look at the FADS genes over the past few years (as well as others at CTEG). These are three nearby genes, FADS1FADS2, and FADS3 (they probably underwent duplication). These genes are involved in the metabolization of fatty acids, and dietary regime turns out to have a major impact on variation around these loci.

The most recent paper out of the Cornell group, Dietary adaptation of FADS genes in Europe varied across time and geography:

Fatty acid desaturase (FADS) genes encode rate-limiting enzymes for the biosynthesis of omega-6 and omega-3 long-chain polyunsaturated fatty acids (LCPUFAs). This biosynthesis is essential for individuals subsisting on LCPUFA-poor diets (for example, plant-based). Positive selection on FADS genes has been reported in multiple populations, but its cause and pattern in Europeans remain unknown. Here we demonstrate, using ancient and modern DNA, that positive selection acted on the same FADS variants both before and after the advent of farming in Europe, but on opposite (that is, alternative) alleles. Recent selection in farmers also varied geographically, with the strongest signal in southern Europe. These varying selection patterns concur with anthropological evidence of varying diets, and with the association of farming-adaptive alleles with higher FADS1 expression and thus enhanced LCPUFA biosynthesis. Genome-wide association studies reveal that farming-adaptive alleles not only increase LCPUFAs, but also affect other lipid levels and protect against several inflammatory diseases.

The paper itself can be difficult to follow because they’re juggling many things in the air. First, they’re not just looking at variants (e.g., SNPs, indels, etc.), but also the haplotypes that the variants are embedded in. That is, the sequence of markers which define an association of variants which indicate descent from common genealogical ancestors. Because recombination can break apart associations one has to engage with care in historical reconstruction of the arc of selection due to a causal variant embedded in different haplotypes.

But the great thing about this paper is that in the case of Europe they can access ancient DNA. So they perform inferences utilizing whole genomes from many extant human populations, but also inspect change in allele frequency trajectories over time because of the density of the temporal transect. The figure to the left shows variants in both an empirical and modeling framework, and how they change in frequency over time.

In short, variants associated with higher LCPUFA synthesis actually decreased over time in Pleistocene Europe. This is similar to the dynamic you see in the Greenland Inuit. With the arrival of farmers the dynamic changes. Some of this is due to admixture/replacement, but some of it can not be accounted for admixture and replacement. In other words, there was selection for the variants which synthesize more LCPUFA.

This is not just limited to Europe. The authors refer to other publications which show that the frequency of alleles associated with LCPUFA production are high in places like South Asia, notable for a culture of preference for plant-based diets, as well as enforced by the reality that animal protein was in very short supply. In Europe they can look at ancient DNA because we have it, but the lesson here is probably general: alternative allelic variants are being whipsawed in frequency by protean shifts in human cultural modes of production.

In War Before Civilization Lawrence Keeley observed that after the arrival of agriculture in Northern Europe in a broad zone to the northwest of the continent, facing the Atlantic and North Sea, farming halted rather abruptly for centuries. Keeley then recounts evidence of organized conflict in between two populations across a “no man’s land.”

But why didn’t the farmers just roll over the old populations as they had elsewhere? Probably because they couldn’t. It is well known that marine regions can often support very high densities of humans engaged in a gathering lifestyle. Though not farmers, these peoples are often also not nomadic, and occupy areas as high density. The tribes of the Pacific Northwest, dependent upon salmon fisheries, are classic examples. Even today much of the Northern European maritime fringe relies on the sea. High density means they had enough numbers to resist the human wave of advance of farmers. At least for a time.

Just as cultural forms wane and wax, so do some of the underlying genetic variants. If you dig into the guts of this paper you see much of the variation dates to the out of Africa period. There were no great sweeps which expunged all variation (at least in general). Rather, just as our omnivorous tastes are protean and changeable, so the genetic variation changes over time and space in a difficult to reduce manner. The flux of lifestyle change is probably usually faster than biological evolution can respond, so variation reducing optimization can never complete its work.

The modern age of the study of natural selection in the human genome began around when A Map of Recent Positive Selection In the Human Genome was published. And it continues with methods like SDS, which indicate that selection operates to this day. Not a great surprise, but solidifying our intuitions. In the supplements to the above paper the authors indicate that the focal alleles that they are interrogating exhibit coefficients of selection around ~0.5% or so. This is rather appreciable. The fact that fixation has not occurred indicates in part that selection has reversed or halted, as they noted. But another aspect is that there are correlated responses; the FADS genes are implicated in many things, as the authors note in relation to inflammatory diseases. But I’m not sure that the selection effects of these are really large in any case. I bet there are more important things going on that we haven’t discovered or understood.

Obviously genome-wide analyses are going to continue for the foreseeable future. Ten years ago my late friend Mike McKweon predicted that at some point genomics was going to have be complemented by detailed follow up through bench-work. I’m not sure if we’re there yet, but there are only so many populations you can sequence, and only to a particular coverage to obtain any more information. Some selection sweeps will be simple stories with simple insights. But I suspect many more like FADS will be more complex, with the threads of the broader explanatory tapestry assembled publications by publication over time.

Citation: Ye, K., Gao, F., Wang, D., Bar-Yosef, O. & Keinan, A. Dietary adaptation of FADS genes in Europe varied across time and geography. Nat. Ecol. Evol. 1, 0167 (2017).

August 29, 2012

The eternal question of calorie restriction

Filed under: calorie restriction,Diet,Health — Razib Khan @ 8:22 pm

There’s a lot of buzz about a new paper in Nature (yes, I know there’s always buzz about some Nature paper or other), Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study. You’ve probably heard about calorie restriction before. For me the issue I have with it is that people who are very knowledgeable (i.e., researchers who know a great deal abut human physiology, etc.) have given me contradictory assessments of this strategy of life extension. But it’s not totally crazy, there are serious scientists at top-tier universities who practice calorie restriction themselves. This isn’t the final word, but I wouldn’t be surprised if it is going to take decades for it to resolve itself for humans specifically (because some people will always be, and perhaps rightly, extrapolating from short-lived organisms to humans when it comes to modulations of lifespan in the laboratory).  The New York Times piece had a really strange coda:

Dr. de Cabo, who says he is overweight, advised people that if they want to try a reduced-calorie diet, they should consult a doctor first. If they can handle such a diet, he said, he believes they would be healthier, ...

January 18, 2011

The “science diet”

Filed under: Diet,Health — Razib Khan @ 12:58 am

Cell has an interesting piece, profiling four diets, Cell Culture: New Year’s Diets. I know many of the readers of this weblog take an interest in this area. In particular, many subscribe to the Paleo diet or are avid fans of Gary Taubes’ Good Calories, Bad Calories, as well as Art Devany’s ideas. Personally I think one issue which we need to acknowledge more are individual differences. The returns on the margin for a given diet may differ from person to person. The morbidity cost to someone with a family history of type 2 diabetes who has a weakness for dessert is likely much higher than someone without such a family history.

The Cell article gives a scientific overview of the diets in question, and then has pointers to the scientific literature.

- Atkins diet

Inagaki, T., et al. (2007). Cell Metab. 5, 415–425.

Badman, M.K., et al. (2007). Cell Metab. 5, 426–437.

Ma, W., et al. (2007). J. Neurosci. 27, 3618–3625.

- Flat Belly Diet

The Lipid Messenger OEA Links Dietary Fat Intake to Satiety

- Sensa Diet

Small, D.M., et al. (2005). Neuron 47, 593–605.

Ruijschop, R.M., et al. (2009). J. Agric. Food Chem. 57, 9888–9894.

- ...

December 7, 2010

One diabetes gene to explain it all?

President William Howard Taft

It is the best of times, it is the worse of times. On the one hand the medical consequences of human genomics have been underwhelming. This is important because this is the ultimate reason that much of the basic research is funded. And yet we’ve learned so much. The genetic architecture of skin color has been elucidated, and we’ve seen a clarification of patterns of natural selection in the human genome. The finding last spring of Neandertal admixture in modern human populations is perhaps the most awesome pure science finding of late, coming close to resolving a decades old debate in anthropology. This doesn’t cure cancer, but it does connect the dots about the human past, and that’s not trivial. We are species haunted by our memories, so we might as well get them right!

But all hope is not lost. Research continues. And one area which general surveys of genomic variation have usually shown to be targets of natural selection, and, also have clear and immediate biomedical relevance, is that of metabolism. How we eat, and how we process and integrate the food we eat, is of obvious fitness relevance in the evolutionary and medical senses. It turns out that there is even variation in our saliva which is probably due to natural selection. The combination of diversity in human cuisine and susceptibility to the diseases of modern life indicate possibilities as to the relationship between past selection pressures and contemporary patterns of genetic variation. Of course one has to tread softly in this area, there are the inevitable confounds of environment, as well the unfortunate probability of any given locus being of small effect size in its influence on any given trait.

ResearchBlogging.orgA new paper in Genome Research reports a SNP which seems to have been subject to natural selection in Eurasians within the last 10,000 years. This variant is located within an exon on a gene, GIP, which produces peptides critical in the regulation of various metabolic pathways, in particular insulin response. A possible biomedical relevance to risk susceptibility is then explored subsequent to the evolutionary genomic preliminaries. Adaptive selection of an incretin gene in Eurasian populations:

Diversities in human physiology have been partially shaped by adaptation to natural environments and changing cultures. Recent genomic analyses have revealed single nucleotide polymorphisms (SNPs) that are associated with adaptations in immune responses, obvious changes in human body forms, or adaptations to extreme climates in select human populations. Here, we report that the human GIP locus was differentially selected among human populations based on the analysis of a nonsynonymous SNP (rs2291725). Comparative and functional analyses showed that the human GIP gene encodes a cryptic glucose-dependent insulinotropic polypeptide (GIP) isoform (GIP55S or GIP55G) that encompasses the SNP and is resistant to serum degradation relative to the known mature GIP peptide. Importantly, we found that GIP55G, which is encoded by the derived allele, exhibits a higher bioactivity compared with GIP55S, which is derived from the ancestral allele. Haplotype structure analysis suggests that the derived allele at rs2291725 arose to dominance in East Asians ∼8100 yr ago due to positive selection. The combined results suggested that rs2291725 represents a functional mutation and may contribute to the population genetics observation. Given that GIP signaling plays a critical role in homeostasis regulation at both the enteroinsular and enteroadipocyte axes, our study highlights the importance of understanding adaptations in energy-balance regulation in the face of the emerging diabetes and obesity epidemics.

This is a paper with several moving parts.

-There is genomics (the broad sweep of the genome)

-Genetics (a focus on a few genes and their consequences)


-And some allusion to epidemiology, as befits a paper which comes out of a medical department

The first observation is that rs2291725 differs a great deal across populations. As I said, it’s a SNP on an exon in GIP. Not only that, it’s nonsynonomous, which means that it’s in a position to change the structure and therefore function of the biochemical which the sequence is ultimately coding for. The T allele is the ancestral variant, while the C allele is the derived one. That means that C arose as a mutation against the background of T. There is a figure which shows the geographical distribution of the variance on this SNP from the HGDP data set in the paper, but I think the HGDP browser produces a crisper display, so here it is:


As you can see the ancestral allele is dominant in Africa. In several populations it is fixed. In contrast among non-African populations there’s quite a bit of variation. In East Asia the derived variant is at a high frequency, though not fixed. In West Eurasia and North Africa the two variants are at rough balance, more or less. Finally, in the New World the derived variant is found in appreciable proportions, but the ancestral variant of the SNP is found at much higher proportions than in other non-African populations. Seeing as how Amerindians derive from a branch of East Eurasians, common descent from an ancestor with the derived allele can not explain the frequency discrepancy. Interestingly the HGDP Melanesians have amongst the highest frequencies of the derived allele in the data set.

In any case, most of the analysis was not done with the HGDP sample, but with the first two phases of the HapMap. The marker density is richer in this sample, and obviously it is easier to compare a few populations than dozens. So the primary populations of comparison in this study were the Chinese + Japanese (ASN), Utah Whites (CEU), and Yoruba from Nigeria (YRI). It was immediately noticeable that when doing pairwise comparisons between two populations in the HapMap data set that the SNP of interest in GIP was exceptional in between population difference when set against other nonsynonymous SNPs. The chart below shows the SNP in red, with the full distribution curve of Fst (proportion of between population difference) illustrated by the bars in blue. rs2291725 is the top 0.5% of Fst difference between ASN and YRI.


The expected Fst between continental races is on the order of ~0.15. The ASN vs. YRI difference is far greater than that, and even more exceptional when you note the skew of the distribution. As it happens there’s HapMap3 data on this SNP as well. It doesn’t add much value to the HGDP, but does confirm the general findings:


Population descriptors:
ASW (A): African ancestry in Southwest USA
CEU (C): Utah residents with Northern and Western European ancestry from the CEPH collection
CHB (H): Han Chinese in Beijing, China
CHD (D): Chinese in Metropolitan Denver, Colorado
GIH (G): Gujarati Indians in Houston, Texas
JPT (J): Japanese in Tokyo, Japan
LWK (L): Luhya in Webuye, Kenya
MEX (M): Mexican ancestry in Los Angeles, California
MKK (K): Maasai in Kinyawa, Kenya
TSI (T): Tuscan in Italy
YRI (Y): Yoruban in Ibadan, Nigeria

Now that they’ve established between population variation at the SNP, what about the structure around the SNP? Remember, the SNP is one base pair. T in the ancestral state, C in the derived. The patterns of variation flanking the SNP in GIP can tell us a lot. What they found was this:

- Africans have several different haplotypes around the T allele. A haplotype is just a set of correlated markers

- The C allele in East Asians seem to be embedded within one haplotype, or set of markers

- There was a lot of linkage disequilibrium around the C allele in East Asians

In East Asians both EHH and iHS were consistent with, if not necessarily suggestive of, selection. A plausible scenario is that the C allele was subject to a powerful bout of natural selection recently, and the allele rose so rapidly in frequency that a selective sweep dragged along the flanking regions of the genome. This would homogenize the variance in that genic region within the population in question (East Asians), as the numerous other haplotypes would decline in proportion. To show the relationships of the various haplotypes within the three HapMap populations being analyzed here they produced an unrooted tree. Observe that the haplotype in which the derived variant is embedded has only Asians and Europeans, and is on a separate branch by itself:


I noted above that just because there is a lot of linkage disequilibrium and haplotype block structure in this region of the genome, it doesn’t necessarily mean that it was a target of natural selection. There may have been stochastic phenomenon which produced these results, and so our inference would be a false positive. To check for this they ran several models and simulations which varied demographic parameters under neutral (non-selective) conditions, and for the Asian sample the iHS scores were generally not as low as those for the SNP of interest. This does not “prove” that demography can not explain these results, but it does shift the probability more toward natural selection than before.

The circumstantial evidence presented above is that the derived allele rose to frequency relatively recently (in general LD decays rapidly over time, so these tests detect more recent selective or demographic events). They ran a simulation under neutral parameters, and for the frequency of the derived haplotype it would take 100-500,000 years for the various populations to reach the values which we see (starting from the initial mutant gene copy). The latter figure is outside the bounds of modern humanity, while the former probably pre-dates the ”Out of Africa” event. It is implausible that so much haplotype structure could be preserved over time, because recombination over the generations breaks apart associations between markers. Using the recombination rates, which would slowly degrade long haplotypes in the genome, the authors inferred that the C allele and its haplotype began to rise in frequency on the order of 12-2,000 years before the present.

Why would an allele rise to frequency within the past 10,000 years? The authors gave the game away in the abstract: humans shifted to different modes of primary production after the rise of agriculture. This is where the role of GIP in producing peptides which have a role in regulating our biochemistry is relevant. GIP is of a class of hormones found in the intestine called incretins:

Incretins are a group of gastrointestinal hormones that cause an increase in the amount of insulin released from the beta cells of the islets of Langerhans after eating, even before blood glucose levels become elevated. They also slow the rate of absorption of nutrients into the blood stream by reducing gastric emptying and may directly reduce food intake. As expected, they also inhibit glucagon release from the alpha cells of the Islets of Langerhans….

500px-Incretins_and_DPP_4_inhibitors.svgIncreased insulin reduces blood sugar. Diabetes is a malfunction of the insulin release mechanism, and so blood sugar begins to rise as individuals don’t uptake their glucose. Glucagon has the opposite effect, increasing blood sugar. But just because there is a change in a nonsynonymous position in an exonic region of a gene of relevance to the pathway, it doesn’t mean that that necessarily impacts the pathway which is illustrated to the left. And for natural selection to have any traction it needs to have an impact on some sort of concrete biological process (unless we’re talking intra-genomic competition of some sort).

It turns out that rs2291725 is actually just outside the primary coding region for the GIP peptide. For it to be a functional variant there needs to be more to the story. As it turns out, there are other less common variants which ware modified by changes at this SNP, GIP55S and GIP55G. The first is produced by the ancestral T allele, and the second by the derived C allele. GIP55S and GIP55G are also found in the intestine, though they only constitute a few percent of the total GIP.

gipactBut here’s where it gets really interesting: GIP55G exhibits more bioactivity over the long term. In other words it seems to be more potent the generic GIP or GIP55S, the ancestral variant. They’ve gone from supposition based on the functional significance of the broader gene, to a connection between the T→C transition over the last 10,000 years. As it turns out it may be that those with GIP55G would have a stronger insulin response, and so reduce blood sugar faster, than those without.

It doesn’t take a genius to figure out where there’re going with this. The relationship between insulin response and carbohydrates in our day and age is fraught. But we already suspect that carbs have reshaped the human genome through copy number variation in the amylase gene. It is interesting though that the derived variant has not fixed. That is, it hasn’t replaced the ancestral variant. This may be due to dominance, so that one copy is almost as efficacious as two, or, it may be due to balancing selection of some sort, which the authors suggest in the text. At this point it’s time to jump to the discussion and let the authors speak for themselves. They start out well:

Based on the gene age estimation and biochemical analyses, our study revealed a functional mutation that is associated with the selection of the GIP locus in East Asian populations ~8100 yr ago and the presence of a cryptic GIP isoform. Specifically, we showed that the inventory of human GIP peptides has recently diverged and that individuals could express three different combinations of GIP isoforms (GIP, GIP55S, and GIP55G) with distinct bioactivity profiles. Future study of how this phenotypic variation affects glucose and lipid homeostasis in response to different diets and of which physiological variations in humans can be attributed to prior gene–environmental interactions at the GIP locus is crucial to a better understanding of human adaptations in energy-balance regulation.

As I observed above many of the researchers have a biomedical background, and the NIH is funding this. The evolutionary anthropological findings, cautious as they are, are fascinating and of deep interest. But I don’t think this is going to go anywhere:

It was hypothesized by Neel almost 50 yr ago that mismatches between prior physiological adaptations and contemporary environments can lead to health risks because the ancestral variants that have been selected for the organism’s fitness or reproductive success may not be optimal for the individual’s health in the new environment…In support of this thrifty genotype hypothesis, a number of genes in humans and house mice have been implied to have coevolved with the emergence of agricultural societies…and a rapid shift in diets is associated with the detrimental effects on human survival in a number of human populations…Conceptually, the serum-resistant GIP55G carried by the GIP103C haplotype may have been beneficial for individuals who have unconstrained access to the food supply in many agricultural societies by preventing severe hyperglycemia. As selection pressure changed in these societies, the ancient GIP103T haplotype could have become a liability and conferred a loss of fitness in the new environment. In addition, we speculate that the selection of GIP in East Asians may contribute to the heterogeneity in the risk of diabetes among major ethnic groups at the present time….

Do you believe that the Han Chinese have had a surfeit of food compared to Africans over the past 10,000 years? Or compared to Europeans? Indians have had more food than Africans? The populations of the New World are in a food-poor environment? This doesn’t make any sense as an evolutionary explanation because the stable state for most of human history has been one of Malthusianism. A few people had a lot of food, ergo, the association of wealth with corpulence. Additionally, one can imagine that societies transitioning between modes of production would have a period when land would be in surplus and there was a lot of food. But for most of history life was grinding. This is simply an unbelievable story. Additionally, this SNP can’t explain most of the variation in diabetes. South Asians have the highest rates in the world, but they have appreciable proportions of the derived variant. I am of the CC (derived-derived) genotype myself (I justed checked on 23andMe), and I have a family risk of diabetes, so I know to ignore the relevance of these findings for myself when it comes to personal risk assessment.

There is probably not going to be one gene that explains diabetes, or obesity, etc. We already knew that, but there is a strange kabuki theater which goes on whereby research groups pretend as to the high significance of one locus, because how is it going to look to a granting agency that you’re out or explain ~1% of the variance in a trait for trivial predictive value? And yet usually they’re honest enough in the discussions to suggest that one finding needs to be integrated into a broader picture…as in the hundreds of other genes of interest!?!?!

This paper is fascinating as a work of human evolutionary history. They don’t have a good story, but they have results which need to be integrated into the bigger framework. But the paper is also a story of the culture of science today, driven by biomedical relevances which are often simply phantoms.

Citation: Chang CL, Cai JJ, Lo C, Amigo J, Park JI, & Hsu SY (2010). Adaptive selection of an incretin gene in Eurasian populations. Genome research PMID: 20978139

November 25, 2010

Eating, and eating well

Filed under: Blog,Diet — Razib Khan @ 12:33 am

Credit: tuchodi

Happy Thanksgiving Day to all the Americans out there. This is a day to loosen the belt a bit, but after the Holidays you probably want to think about slimming back. So, ScienceDaily, Obesity Riddle Finally ‘Solved’, and, Diets with High or Low Protein Content and Glycemic Index for Weight-Loss Maintenance. The upshot seems to be that a high protein-low (refined) carb diet worked best in a large sample of Europeans.

Myself, I was in the 155-165 pound range between 2000 and 2007. 2008-2010 I’ve been in the 140-150 range, and usually closer to the low end than the high. I went from a waist size in the 31-33 inch range to 28-30 range (I wear 28s regularly now). I’m moderately active in that I walk a lot, but I have totally turned away from refined carbs. I am not a religious ‘Paleo’, but I do track glycemic indices and glycemic loads for various foods rather closely. That being said, different people have different biologies. I think that’s important to remember. As a South Asian I have a higher risk for type 2 diabetes, so I’m particularly vigilant about sugar and other variables which increase my probabilities for chronic diseases. If I was a Northern European I might have different priorities, and chill out a little bit about dessert. Life is about trade-offs, and pleasures do often have costs. I am not much of a sweet-tooth, and I’m genetically predisposed to type 2, so my aversion toward sweets is a rather simple calculation. Others may have different outcomes performing the same operations because of different inputs. The answer to a riddle may vary depending on who is asking.

April 8, 2010

Evolutionary fitness & nutrition

Filed under: Diet,Genetics,Human Evolution,Nutrition — Razib @ 7:37 pm

Russ Roberts recently had a discussion on Econtalk with Arthur de Vany. A lot of it covered baseball and social science, but he also spent a lot of time on “evolutionary fitness” (see the website at the link). I agree with a lot of what he had to say, but felt that some of his assertions about past evolutionary history exhibited too much certitude in the consensus of the field. In particular, when it comes to nutrition I think that evolutionary informed diets may need to take into account individual differences more than they do. I think there’s an unfortunate tendency of many people who find a particular diet which works for them to strongly extrapolate the efficacy of that diet to everyone else to the same extent. Probably limiting strong advice to near relatives would get rid of most of my concerns since families would share many of the same predispositions.


March 2, 2010

Eating like your ancestors

Filed under: Diet,Genetics,Genomics,Health — Razib @ 7:13 pm

The ideas of gene-culture coevolution have percolated all the way to the foodie-sphere, over at Epi-Log at Epicurious, The Health Trend of the Future: The Ethnic-Group Diet?:

So, maybe at some point in the future, a visit to the doctor will involve a full genetic workup followed by a prescribed diet tailored to our individual makeup. I might be advised to eat lots of whole grains and dairy products, while someone else might do better on mostly meat and vegetables. This is probably a long way off though—there’s still a lot of science to be filled in.

The “low hanging fruit” like lactose tolerance has been around a long time. Gary Nabhan wrote Why Some Like It Hot: Food, Genes, and Cultural Diversity in 2004. In any case, family background is obviously going to be important, but information from your ethnic background is also probably useful, especially if you have a small family. Ultimately nutrigenomics might advance far enough that we can get personalized recommendations, but if much of the genetic variation is part of the missing heritability than population-level information might be critical for a long time to come. Additionally, population-level information might be relevant as genetic variations which we know about may expression differently conditional on genetic background.

But a consideration that’s not totally trivial is that diets can change very fast. The Columbian Exchange resulted in the introduction of chili peppers to much of Asia, to the point where the extent of their usage in the local cuisine can be diagnostic as to regional origin. And of course potatoes are a relatively new staple in much of Europe. Though in both of these cases the basic nutritional value or culinary role simply substitutes for what was already on hand, starch in the case of the potato and spice in the case of chili pepper.


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