Evidence for Natural Selection in Humans: East Asians Have Higher Frequency of CASC5 Brain Size Regulating Gene
Brain size is one physical difference that the races differ on. East Asians have bigger brains than Europeans who have bigger brains than Africans (Beals et al, 1984; Rushton, 1997). What caused these average differences and the ultimate causes for them have been subject to huge debate. Is it drift? Natural/sexual selection? Mutation? Gene flow? Epigenetic? One reason why brains would need to be large in colder climates is due to heat retention, while in tropical climates heads need to be smaller to dissipate heat. One of the biggest criticisms of HBD is that there is no/little evidence of recent natural selection between human races. Well, that has changed.
CASC5 “performs two crucial functions during mitosis, being required for correct attachment of chromosome centromeres to the microtubule apparatus, and also essential for spindle-assembly checkpoint (SAC) signaling” (Shi et al, 2016). The gene has been found to be important in recent human evolution along with neurogenesis.
Shi et al (2016) genotyped 278 Han Chinese (174 females and 104 males with a mean age of 36) who were free of maladies or genetic defects. They had the coding sequences of CASC5 for humans, chimpanzees, gorillas, baboons, gibbons, orangutans, tarsiers, Denisovans, and Neanderthals. They downloaded genotypes from the Human Genome Project for their analysis.
They compared CASC5 among three human species: humans, Neanderthals, and Denisovans. Using chimpanzees as an outgroup, they discovered 45 human-specific mutations, 48 Neanderthal-specific mutations, and 41 Neanderthal-specific mutations. Further, when one exon region was aligned among modern humans, non-human primates and other mammalian species, 12 amino acid sites showed divergence between modern humans, Neanderthals, and Denisovans with 8 occurring in modern humans. Of the 8 sites in humans, 6 are preserved which implies that they were important in our evolutionary history.
Shi et al (2016) write:
At the population level, among the 8 modern human amino acid changes, two (H159R and G1086S) are fixed in current human populations, and the other six are polymorphic Fig. 1). Surprisingly, 5 of the 6 amino acid polymorphic sites showed deep between-population divergence in allele frequencies. East Asians possess much higher frequencies of the derived alleles at four sites (T43R-rs7177192, A113T-rs12911738, S486A-rs2412541 and G936R-rs8040502) as compared to either Europeans or Africans (Fig. 1), while E1285K-rs17747633 is relatively enriched in Europeans (46%), and rare in East Asians (10%) and Africans (3%). No between-population divergence was observed for T598 M-rs11858113 (Fig. 1).
So East Asians have a much higher frequency of this derived trait. This is direct evidence for natural selection in recent human evolution in regards to the physical structure of the brain.
Since most of the amino acid polymorphic sites showed between-population divergence, they decided to analyze the three classical races using 1000 genomes. The variation between the races could be due to either genetic drift or natural selection. When they analyzed certain gene regions, they observed a signal of positive selection for East Asians but not Europeans or Africans. They further tested this selection signal using “the standardized integrated haplotype score (iHS) which is used for detecting recent positive selection with incomplete sweep (i.e. the selected allele is not yet fixed)” (Shi et al, 2016). Using this method, they discovered a few SNPs with large iHS values in Europeans (7 SNPs at 4.2 percent) and none in Africans.
They also conducted a genome-wide scan of Fst, iHS, and “XPCLR (searching for highly differentiated genomimc regions as targets of selective sweeps)” (Shi et al, 2016). Several SNPs had high Fst, iHS and XPCLR scores, which indicate that these alleles have been under positive selection in East Asians. Among the fixed amino acid sites in human populations, East Asians showed 5, Europeans showed 1, and Africans showed 0 which, the authors write, “[imply] that these amino acid changes may have functional effects” (Shi et al, 2016). Furthermore, using the HDGP, they obtained the frequency of the 6 amino acid sites in 53 populations. This analysis showed that 4 of the 6 amino acid sites are “regionally enriched in East Asia .. in line with the suggested signal of population-specific selection in this area” (Shi et al, 2016).
Then, since CASC5 is a brain size regulating gene, they looked for phenotypic effects. They recruited 167 Han Chinese (89 men, 178 women) who were free of maladies. They genotyped 11 SNPs and all of the frequencies followed Harvey-Weinberg Equilibrium (which states that allele and genotype frequencies will remain constant in a population from generation to generation in the absence of evolutionary pressures; Andrews, 2010). In the female sample, 5 regions were related to gray matter volume and four were on the amino acid polymorphic sites. Interestingly, the four alleles which showed such a stark difference between East Asians and Europeans and Africans showed more significant associations in Han Chinese females than males. Those carrying the derived alleles had larger brain volumes in comparison with those who had the ancestral alleles, implying recent natural selection in East Asia for brain size.
Shi et al (2015) also attempted two replications on this allele writing:
We further conducted a replication analysis of the five significant CAC5 SNPs in two other independent Han Chinese samples (Li et al. 2015; Xu et al. 2015). The results showed that three SNPs (rs 7177192, rs11858113 and rs8040502) remained significant in Replication-1 for total brain volume and gray matter volume (Xu et al. 2015), but no association was detected in Replication-2 (Li et al. 2015) (Table S4).
It is very plausible that the genes that have regulated brain growth in our species further aid differences in brain morphology within and between races. This effect is seen mostly in Han Chinese girls. Shi et al (2016) write in the Discussion:
If this finding is accurate and can be further verified, it suggests that that [sic] after modern humans migrated out of Africa less than 100,000 years ago, the brain size may still be subject to selection.
I do believe it is accurate. Of course, the brain size could still be subject to selection; there is no magic field shielding the brain against selection pressure. Evolution does not stop at the neck.
So Shi et al (2016) showed that there were brain genes under recent selection in East Asians. What could the cause be? There are a few:
- Climate: In colder climates you need a smaller body size and big brain to survive the cold to better thermoregulate. A smaller body means there is less surface area to cover, while a larger head retains heat. It, obviously, would have been advantageous for these populations to have large brains and thus get selected for them—whether by natural or sexual selection. This could also have to do with the fact that one needs bigger eyes in colder environments, which would cause an increase in the size of the brain for the larger eyes, as well as being sharper visio-spatially.
- Intelligence: East Asians in this study showed that they had high levels of gray matter in the skull. Further, large brains are favored by an intermediately challenging environment (Gonzalez-Forero, Faulwasser, and Lehmann, 2017).
- Expertise: I used Skoyle’s (1999) theory on expertise and human evolution and applied it to racial differences in brain size and relating it to the number of tools they had to use which differed based on climate. Now, of course, if one group uses more tools then, by effect, they would need more expertise with which to learn how to make those tools so large brains would be selected for expertise—especially in novel areas.
- Vision: Large brains mean large eyes, and people from cold climates have large eyes and large brains (Pearce and Dunbar, 2011). Decreasing light levels select for larger eye size and visual cortex size in order to “increase sensitivity and maintain acuity“. Large eyeballs mean enlarged visual cortices. Therefore, in low light, large brains and eyes get selected for so one can see better in a low light environment.
Of course, all four of the examples below could (and probably do) work in tandem. However, before jumping to conclusions I want to see more data on this and how the whole of the system interacts with these alleles and these amino acid polymorphic sites.
In sum, there is now evidence for natural selection on East Asians (and not Africans or Europeans) that favored large brains, particularly gray matter, in East Asians with considerable sexual dimorphism favoring women. Four of the genes tested (MCPH1, ASPM, CDK5RAP2, and WDR62) are regulated by estradiol and contribute to sexual dimorphism in human and non-human primates (Shi et al, 2016). Though it still needs to be tested if this holds true for CASC5.
This is some of the first evidence that I have come across for natural selection on genes that are implicated in brain evolution/structural development between and within populations. It does show the old “Rushton’s Rule of Three“, that is, Mongoloids on top, Caucasians in the middle, and Negroids on bottom, though Caucasians were significantly closer to Africans than Mongoloids in the frequency of these derived alleles. I can see a HBDer going “They must be related to IQ”, I doubt it. They don’t ‘have’ to be related to IQ. It just infers a survival advantage in low light, cold environments and therefore it gets selected for until it reaches a high frequency in that population due to its adaptive value—whether spreading by natural or sexual selection.
When I first got into HBD back in 2012, one of the first things I came across—along with the research on racial IQs from Rushton, Lynn, Jensen et al—was that the races differed in a gene called MAOA-L, which has a frequency in Caucasians at .1 percent (Beaver et al, 2013), 54 percent in Chinese people (Lu et al, 2013; as well as 77 percent for the 3r MAOA allele; Lea and Chambers, 2007), 56 percent in Maoris (Lea and Chambers 2007) while about 60-65 percent of Japanese people have the low-frequency version of this gene (Way and Lieberman, 2007).
So if these ethnies have a higher rate of this polymorphism and it is true that this gene causes crime, then the Chinese and Japanese should have the highest rates of crime in the world, since even apparently the effect of MAOA and violence and antisocial behavior is seen even without child abuse (Ficks and Waldman, 2014). Except East Asian countries have lower rates of crime (Rushton, 1995; Rushton and Whytney, 2002). Though, Japan’s low crime rate is relatively recent, and when compared with other countries on certain measures “Japan fares the same or worse when compared to other nations” (Barberet 2009, 198). This goes against a lot of HBD theory, and I will save that for another day. (Japan has a 99 percent prosecution rate, which could be due to low prosecutorial budgets; Ramseyer and Rasmusen, 2001. I will cover this in the future.)
The media fervor—as usual—gave the MAOA gene the nickname “the warrior gene“, which is extremely simplistic (I will have much more to say on ‘genes for’ any trait towards the end of the article). I will show how this is a very simplistic view.
The MAOA gene was first discovered in 1993 in a Dutch family who had a history of extreme violence going as far back as the 1890s. Since the discovery of this gene, it has been invoked as an ultimate cause of crime. However, as some hereditarians do note, MAOA only ’causes’ violence if one has a specific MAOA genotype and if they have been abused as a child (Caspi et al, 2002; Cohen et al, 2006; Beaver et al, 2009; Ferguson et al, 2011; Cicchetti, Rogosch, Thibodeau, 2012;). People have invoked these gene variants as ultimate causes of crime—that is, people who have the low-expressing MAOA variants are more likely to commit more crime—but the relationship is not so simple.
Maoris are more four times more likely to have the low-expressing gene variant than Europeans, the same holding for African Americans and Europeans (Lea and Chambers, 2007).
There is, however, a protective effect that protects whites (and not non-whites in certain cases) against antisocial behavior/violent attitudes if one has a certain genotype (Widom and Brzustowicz, 2006), though the authors write on page 688: “For non-whites, the effect of child abuse and neglect on the juvenile VASB was not significant (beta .08, SE .11, t 1.19, ns), whereas the effect of child maltreatment on lifetime VASB composite approached significance (beta .13, SE .12, t 1.86, p .06). For non-whites (see Figure 2), neither gene (MAOA) environment (child abuse and neglect) interaction was significant: juvenile VASB (beta .06, SE .28, t .67, ns) and lifetime VASB (beta .01, SE .29, t .14, ns).” So as you can see, there are mixed results. Whites seem to be protected against the effect of antisocial behavior and violence but only if they have a certain genotype (which implies that if they have the other genotype, then if abused they will show violent and antisocial behavior). So, we can see that the relationship between MAOA and criminal behavior is not as simple as some would make it out to be.
MAOA, like other genetic variants, of course, has been linked to numerous other traits. Steven J. Heine, author of the book DNA is Not Destiny: The Remarkable and Completely Misunderstood Relationship Between You and Your Genes:
However, any labels like “the warrior gene” are highly problematic because they suggest that the this gene is specifically associated with violence. It’s not, just as alleles from other genes do not only have one outcome. Pleiotropy is the term for how a single genetic variant can influence multiple different phenotypes. MAOA is highly pleiotropic: the traits and conditions potientially connected to the MAOA gene invlude Alzheimer’s. anoerxia, autism, body mass index, bone mineral density, chronic fatigue syndrome, depression, extraversion, hypertension, individualism, insomnia, intelligence, memory, neuroticism, obesity, openness to experience, persistence, restless leg syndrome, schizophrenia, social phobia, sudden infant death syndrome, time perception and voting behavior. (59) Perhaps it would be more fitting to call MAOA “the everything but the kitchen sink gene. (Heine, 2017: 195)
Something that I have not seen brought up when discussions of race, crime, and MAOA come up is that Japanese people have the highest chance—even higher than blacks, Maoris, and whites—to have the low repeat MAOA variant (Way and Lieberman) yet have lower rates of crime. So MAOA cannot possibly be a ‘main cause’ of crime. It is way more complex than that. “However intuitively satisfying it may be to explain cultural differences in violence in terms of genes“, Heine writes, “as of yet there is no direct evidence for this” (Heine, 2017: 196).
Numerous people have used ‘their genes’ in an attempt to get out of criminal acts that they have committed. A judge even knocked off one year off of a murder’s sentence since he found the evidence for the MAOA gene’s link to violence “particularly compelling.” I find it “particularly ridiculous” that the man got less time in jail than someone who ‘had a choice’ in his actions to murder someone. Doesn’t it seem ridiculous to you that someone gets less time in jail than someone else, all because he may have the ‘crime/warrior gene’?
Aspinwall, Brown, and Tabery (2012) showed that when evidence of a ‘biomechanic’ cause of violence/psychopathy was shown to the judges (n=191), that they reduced their sentences by almost one year if they were reading a story in which the accused was found to have the low-repeat MAOA allele (13.93 to 12.83 years). So, as you can see, this can sway judges’ perception into giving one a lighter sentence since they believe that the evidence shows that one ‘can not control themselves’, which results in the judge giving assailants lighter sentences because ‘it’s in their genes’.
Further, people would be more lenient on sentences for criminals who are found to have these ‘criminal genes’ than those who were found to not have them (Cheung and Heine, 2015). Monterosso, Royzman, and Schwartz (2010) also write: “Physiologically explained behavior was more likely to be characterized as “automatic,” and willpower and character were less likely to be cited as relevant to the behavior. Physiological explanations of undesirable behavior may mitigate blame by inviting nonteleological causal attributions.” So, clearly, most college students would give a lighter sentence if the individual in question were found to have ‘criminal genes’. But, if these genes really did ’cause’ crime, shouldn’t they be given heavier sentences to keep them on the inside more so those with the ‘non-criminal genes’ don’t have to suffer from the ‘genetically induced’ crime?
Heine (2017: 198-199) also writes:
But is someone really less any responsible for their actions if his or her genes are implicated? A problem with this argument is that we would be hard-pressed to find any actions that we engage in where our genes are not involved—our behaviors do not occur in any gene-free zones. Or, consider this: there actually is a particular genetic variant that, if you possess it, makes you about 40 times more likely to engage in same-sex homicides than those who possess a different variant. (66) It’s known as the Y chromosome—that is, people who possess it are biologically male. Given this, should we infer that Y chromosomes cause murders, and thus give a reduced sentence to anyone who is the carrier of such a chromosome because he is really not responsible for his actions? The philosopher Stephen Morse calls the tendency to excuse a crime because of a biological basis the “fundamental psycholegal error.” (67) The problem with this tendency is that it involves separating yout genes from yourself. Saying “my genes made me do it” doesn’t make sense because there is no “I” that is independent of your genetic makeup. But curiously, once genes are implicaed, people see, to feel that the accused is no longer fully in control of his or her actions.
Further, in the case of a child pornographer, one named Gary Cossey, the court said:
The court predicted that some fifty years from now Cossey’s offense conduct would likely be discovered to be caused by “a gene you were born with. And it’s not a gene you can get rid of.” The court expressed its belief that although Cossey was in therapy, it “can only lead, in my view, to a sincere effort on your part to control, but you can’t get rid of it. You are what you’re born with. And that’s the only explanation for what I see here.”
However, this judge punished Cossey more severely due to the ‘possibility’ that scientists may find ‘genes for’ child pornography use in 50 years. Cossey was then given another, unbiased judge, and was given a ‘more lenient’ sentence than the genetic determinist judge did.
Sean Last over at The Alternative Hypothesis is also a big believer in this so-called MAOA-race difference that explains racial differences in crime. However, as reviewed above (and as he writes), MAOA can be called the “everything but the kitchen sink gene” (Heine, 2017: 195), as I will touch on briefly below, to attribute ’causes’ to genes is not the right way to look at them. It’s not so easy to say that since one ‘has the warrior gene’ that they’d automatically be violent. Last cites a study saying that even those who have the MAOA allele who were not abused showed higher rates of violent behavior (Ficks and Waldman, 2014). They write (pg. 429):
The frequency of the ‘‘risk’’ allele in nonclinical samples of European ancestry ranges from 0.3 to 0.4, although the frequency of this allele in individuals of Asian and African ancestry appears to be substantially higher (*0.6 in both groups; Sabol et al. 1998).
So, why don’t Asians have higher rates of crime—along with blacks—if MAOA on its own causes violent and antisocial behavior? Next I know that someone would claim that “AHA! TESTOSTERONE ALSO MEDIATES THIS RELATIONSHIP!!” However, as I’ve talked about countless times (until I’m blue in the face), blacks do not have/have lower levels of testosterone than whites (Richards et al, 1992; Gapstur et al, 2002; Rohrmann et al, 2007; Mazur, 2009; Lopez et al, 2013; Hu et al, 2014; Richard et al, 2014). Though young black males have higher levels of testosterone due to the environment (honor culture) (Mazur, 2016). So that canard cannot be trotted out.
All in all, these simplistic and reductionist approaches to ‘figuring out’ the ’causes’ of crime do not make any sense. To point at one gene and say that this is ‘the cause’ of that do not make sense.
One last point on ‘genes as causes’ for behavior. This is something that deserves a piece of its own, but I will just provide a quote from Eva Jablonska and Marion Lamb’s book Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life (Jablonska and Lamb, 2014: 17; read chapter one of the book here; I have the nook version so the page number may be different):
Although many psychiatrists, biochemists, and other scientists who are not geneticists (yet express themselves with remarkable facility on genetic issues) still use the language of genes as simple causal agents, and promise their audience rapid solutions to all sorts of problems, they are no more than propagandists whose knowledge or motives must be suspect. The geneticists themselves now think and talk (most of the time) in terms of genetic networks composed of tens or hundreds of genes and gene products, which interact with each other and together affect the development of a particular trait. They recognize that whether or not a trait (a sexual preference, for example) develops does not depend, in the majority of cases, on a difference in a single gene. It involves interactions among many genes, many proteins and other types of molecule, and the environment in which an individual develops.
So to say that those who have low-functioning MAOA variants have an ‘excuse’ as to why they commit crime is incorrect. I know that most people know this, but when you read some people’s writings on things like this it’s like they think that these singular genes/polymorphisms/etc cause these things on their own. In actuality, you need to look at how the whole system interacts with these things, and not reduce whole complex physiological systems to a sum of its parts. This is why implicating singular genes/polymorphisms as explanations for racial differences in crime does not make sense (as can be seen with the Japanese example).
To reduce behaviors simply to gene X and not look at the whole system does not make any sense. There are no ‘genes for’ anything, except a few Mendelian diseases (Ropers, 2010). Stating that certain genes ’cause’ X, as I have shown does not make sense and, wrongly, in my opinion, gives criminals less of a sentencing since judges find stuff like this ‘very compelling’. If that’s the case, why implicate any murderer? ‘Their genes made them do it’, right? Though, things are not that simple to implicate one gene as a cause for crime or any other complex behavior; in this sense—like for most things to do with the human body—holism makes way more sense and not reductionism. We need to look at how these genes that are ‘implicated’ in criminal behavior interact with the whole system. Only then can we understand the causes of criminal behavior. Looking at singular genes impedes us from figuring out the true underlying reasons why people commit crime.
Remember: we can’t blame “warrior genes” for violent crime. If someone does have a ‘genetic predisposition to crime’ from the MAOA gene, then wouldn’t it make more sense to give them more time? Though, the relationship is not so simple as I have covered. So to close, there is no ‘simple relationship’ between race, crime and MAOA. Not in the way that other hereditarians would like you to believe. Because if this relationship were so simple, then East Asians (Chinese, Japanese) would have the highest rates of crime, and they do not.
The notion that there is any ‘progress’ to evolution is something that I have rebutted countless times on this blog. My most recent entry being Marching Up the ‘Evolutionary Tree’? which was a response to Pumpkin Person’s article Marching up the evolutionary tree. Of course, people never ever change their views in a discussion (I have seen it, albeit it is rare) due, mainly to, in my opinion, ideology. People have so much time invested in their little pet theories that they cannot possibly fathom at the thought of being wrong or being led astray by shoddy hypotheses/theories that confirm their pre-existing beliefs. I will quote a few comments from Pumpkin Person’s blog where he just spews his ‘correlations with brain size and ‘splits’ on the ‘evolutionary tree” that ‘proves that evolution is progressive’, then I will touch on two papers (I will cover both in great depth in the future) that directly rebut his idiotic notion that so-called brain size increases across our evolutionary history (and even before we became humans) are due to ‘progress in evolution’
I think you mistyped that, but i see your point. Problem, however, most of your used phylogenies were unbalanced.
Based on the definition you provided, but not based on any meaningful definition. To me, an unbalanced tree is . . .
This is literally meaningless. Keep showing that you’ve never taken a biology class in your life, it really shows.
All it is is ignorance to basic biological thinking, along with an ideology to prove his ridiculous Rushtonian notion that ‘brain size increases prove that evolution is progressive’.
You have yet to present ANY scientific logic, and my argument about taxonomic specificity is clearly beyond you.
Scientific logic?! Scientific logic?! Please. Berkely has a whole page on misconceptions on evolution that directly rebut his idiotic, uneducated views on evolution. It doesn’t help that his evolution education most likely comes from psychologists. Nevertheless, PP’s ‘argument’ is straight garbage. Taxonomic specificity’ is meaningless when you don’t have an understanding of basic biological concepts and evolution. (I will have much more to say on his ‘taxonomic specificity’ below.)
Was every tree perfect? No, but most were pretty close, and keep in mind that any flawed trees would have the effect of REDUCING the correlation between brain size/encephalization and branching, because random error is a source of statistical noise which obscures any underlying relationship. So the fact that I repeatedly found such robust correlation in spite of alleged problems with my trees, makes my conclusions stronger, not weaker.
The fact that you ‘repeatedly’ found ‘correlations’ in spite of the ‘problems’ with your trees makes your ‘conclusions’ weaker. Comparing organisms over evolutionary time and you notice a ‘trend’ in brain size. Must mean that evolution is progressive and brain size is its calling card!!
I’m right and all the skeptics you cite are wrong.
Said like a true idealogue.
It’s not how many splits they have that I’ve been measuring, it’s how many splits occur on the tree before they branch off. Here’s a source from 2017:
Eukaryotes represent a domain of life, but within this domain there are multiple kingdoms. The most common classification creates four kingdoms in this domain: Protista, Fungi, Plantae, and Animalia.
So you needed ‘a source from 2017’ to tell you something that is literally taught on the first day of biology 101? Keep showing how uneducated you are here.
Nothing fallacious about a correlation between number of splits and brain size/encephalization.
Post hoc, ergo propter hoc is a Latin phrase for “after this, therefore, because of this.” The term refers to a logical fallacy that because two events occurred in succession, the former event caused the latter event.
Magical thinking is a form of post hoc, ergo propter hoc fallacy, in which superstitions are formed based on seeing patterns in a series of coincidences. For example, “these are my lucky trousers. Sometimes good things happen to me when I wear them.”
P1: X happened before Y.
P2: (unstated) Y was caused by something (that happened before Y).
C1: Therefore, X caused Y.
Here is PP’s (fallacious) logic:
P1: splits (X) happened before Y (brain size increase)
P2: (unstated) brain size increase was caused by something (that happened before brain size increaes [splits on the tree])
C1: therefore, splits caused brain size increase
Now, I know that PP will argue that ‘splits on the evolutionary tree’ denote speciation which, in turn, denotes environmental change. This is meaningless. You’re still stating that Y was caused by something (that happened before Y) and therefore inferring that X caused Y. That is the fallacy (which a lot of HBD theories rest on).
You don’t get it. Even statistically insignificant correlations become significant when you get them FIVE TIMES IN A ROW. If you want to believe it was all a coincidence, then fine.
Phylogenies are created from shared derived factors. Berkely is the go-to authority here on this matter. (No that’s not appeal to authority.) Biologists collect information about a given animal and then infer the evolutionary relationship. Furthermore, PP’s logic is, again, fallacious. Berkely also has tips for tree reading, which they write:
Trees depict evolutionary relationships, not evolutionary progress. It’s easy to think that taxa that appear near one side of a phylogenetic tree are more advanced than other organisms on the tree, but this is simply not the case. First, the idea of evolutionary “advancement” is not a particularly scientific idea. There is no unbiased, universal scale for “advancement.” Second, taxa with extreme versions of traits (which might be perceived as more “advanced”) may occur on any terminal branch. The position of a terminal taxon is not an indication of how adaptive, specialized, or extreme its traits are.
He may emphatically argue (as I know he will) that he’s not doing this. But, as can be seen from his article, X is ‘less advanced’ than Y, therefore splits, brain size, correlation=progress. This is dumb.
For anyone who wants to know how (and how not to) read phylogenies, read Gregory (2008). These idotic notions that PP espouses are what Freshman in college believe due to ‘intuitiveness’ about evolution. It’s so rampant that biologists have writen numerous papers on the matter. But some guy with a blog and no science background (and an ideology to hammer) must know more than people who do this for a living (educate people on phylogenies).
On Phil’s response to see the Deacon paper that I will discuss below, PP writes:
That’s not a rebuttal.
Yes it is, as I will show shortly.
The first paper I will discuss is Deacon’s (1990) paper Fallacies of Progression in Theories of Brain-Size Evolution. This is a meaty paper with a ton of great ideas about phylogenies, along with numerous fallacies that people go to when reading trees (my favorite being the Numerology fallacy, which PP uses, see below).
Deacon argues that since people fail to analyze allometry, this anatomists have mistaken artifacts for evolutionary trends. He also argues that many structural’brain size increases’ from ‘primitive to advanced forms’ (take note here, because this is what PP did and this is what discredits his idiotic ideology) are the result of allometric processes.
Source: Evolution of consciousness: Phylogeny, ontogeny, and emergence from general anesthesia Mashour and Alkire (2013)
This paper (and picture) show it all. This notion of scala naturae (which Rushton (2004) attempted to revive with r/K selection theory has been rebutted by me) was first proposed by Aristotle. We now know how the brain structure evolved, so the old ‘simple scala naturae‘ is, obviously, out of date in the study of brain evolution.
This paper is pretty long and I don’t have time to discuss all of it so I will just provide one quote that disproves PP’s ‘study’:
Whenever a method is discovered for simplifying the representation of a complex or apparently nonsystematic numerical relationship, the method of simplification itself provides new insight into the phenomenon under study. But reduction of a complex relationship to a simple statistic makes it far easier to find spurious relationships with other simple statistics. Numerology fallacies are apparent correlations that turn out to be artifacts of numerical oversimplification. Numerology fallacies in science, like their mystical counterparts, are likely to be committed when meaning is ascribed to some statistic merely by virtue of its numeric similarity to some other statistic, without supportive evidence from the empirical system that is being described.
Deacon also writes in another 1990 article titled Commentary on Ilya I. Glezer, Myron So Jacobs, and Peter J Morgane (1988) Implications of the “initial brain’9 concept for brain evolution in Cetacea:
The study of brain evolution is one of the last refuges for theories of progressive evolution in biology, but in this field its influence is still pervasive. To a great extent the apparent “progress” of mammalian brain evolution vanishes when the effects of brain size and functional specialization are taken into account.
(It’s worth noting that in the author’s response to Deacon, he did not have any qualms about ‘progressive brain-size’.)
In regards to PP’s final ‘correlation’ on human races and brain-size, this is a perfect quote from McShea (1994: 1761):
If such a trend [increase in brain size leading to ‘intelligence’] in primates exists and it is driven, that is, if the trend is a direct result of concerted forces acting on most lineages across the intelligence spectrum, then the inference is justified. But if it is passive, that is, forces act only on lineages at the low-intelligence end, then most lineages will have no increasing tendency. In that case, most primate species—especially those out on the right tail of the distribution like ours—would be just as likely to lose intelligence as to gain it in subsequent evolution (if they change at all).
The ‘trend’ is passive. Homo floresiensis is the best example. We are just as likely to lose our ‘intellect’ and our ‘big brains’ as we are to ‘get more intelligent’ and ‘smaller brains’. The fact of the matter is this: environment dictates brain size/whatever other traits an organism has. Imagine a future environment that is a barren wasteland. Kilocalories are scarce; do you think that humans would keep their big brains—which are two percent of their body weight accounting for a whopping 25 percent of total daily energy needs—without enough high-quality energy? When brain size supposedly began to increase in our taxa is when erectus learned to control fire and cook meat (Hlublik et al, 2017).
All in all, there is no ‘progress’ to evolution and, as Deacon argues, so-called brain-size increases across evolutionary time disappear after adjustments for body size and functional specialties are taken into account. However, for the idealogue who looks for everything they can to push their ideology/worldview, things like this are never enough. “No, that wasn’t a rebuttal! YOU’RE WRONG!!” Those are not scientific arguments. If one believes in ‘evolutionary progress’ and that brain-size increases are the proof in the pudding that evolution is ‘progressive’ (re has a ‘direction’), then they must rebut Deacon’s arguments on allometry and his fallacies in his 1990 paper. Stop equating evolution with ‘progress’. Though, I can’t fault laymen for believing that. I can, however, fault someone who supposedly enjoys the study of evolution. You’re wrong. The people you cite (who are out of their field of expertise) are wrong.
Evolution is an amazing process. To equate it with ‘progress’ does not allow one to appreciate the beauty of the process. Evolution does carry baggage with it, and if I weren’t so used to the term I would use Descent by Modification (DbM, which is what Darwin used). Nevertheless, progressionists will hide out in whatever safehold they can to attempt to push their idealogy that is not based on science.
(Also read Rethinking Mammalian Brain Evolution by Terrence Deacon. I go more in depth on these three articles in the future.)
I came across this video on YouTube last night by a geneticist/science writer Steve Jones. He is also the Emeritus Professor of genetics at University College London. This makes what he says in the video I will speak about below very troubling—especially to a man of his caliber with the knowledge he has—views he has on the hormone.
In the very beginning of the video titled Testosterone and Crime: What Can Genes Tell Us About Behavior?, Jones says “But in fact, there are genes—there is a gene—for crime, which causes nearly all the crime, and is widely used and we understand a great deal about it. It’s a chemical gene it produces a particular chemical, which we understand in detail is the chemical testosterone. Testosterone—we all have it but some of us have rather more than others—testosterone is of course a gene that is made—switched on by the Y chromosome and makes males male. Women have a small amount but only a small amount and as they get older … Now testosterone is a dangerous, dangerous thing to have. I don’t recommend it, those of you who have it, don’t get it. And if you’ve got some, don’t get any more.” What bullshit! This guy is a literal genetics Ph.D. saying this; this is proof that knowledge/educational attainment does not stop you from saying dumb, untrue things.
“I don’t know that this character does it, but certainly plenty of bodybuilders inject steroids—testosterone—into themselves. They damage themselves severely. Their life expectancy goes down strikingly. They die for all those male reasons. They die from violence, they die from suicide, they die from car accidents, they die from heart disease, all those things are true of males. … But even if you look at males and females in general, there is kind of a depressing picture for half of the room, I’m not sure which half.” Jones then talks about how men die at a much higher rate than women for a slew of reasons. This is his logic: Men have higher testosterone than women. Testosterone is shown to cause violence, aggression, heart disease, risk-taking, etc. Men have way more testosterone than women. Therefore testosterone is the reason why men die more than women and commit more violence than women. This is horrible logic—coming from a geneticist no less!
“Men actually—less expectedly perhaps—are much less good at dealing with parasites and infectious disease than women are. And that’s because testosterone—the male hormone—suppresses the immune system. Now the immune system fights off the parasites and we don’t do nearly as well.” There is actually some empirical data for his argument here. Back in 2013, it was shown that testosterone, gene expression, and the immune system were linked. They discovered that higher levels of testosterone prevented Module 52 genes from turning on. So higher levels of testosterone result in more Module 52 expression. Testosterone also does exert immune-suppressing effects, “increasing the severity of malaria, leishmaniasis, amebiasis, and tuberculosis, while at the same time supporting the clearance of toxoplasmosis (Bernin & Lotter, 2014; Nhamoyebonde & Leslie, 2014)” (Giefing-Kroll et al, 2015). The suppressive effects of testosterone on the immune system and how down-regulates “the systemic immune response by cell type specific effects in the context of immunological disorders.” (Trigunaite, Dimo, and Jorgensen, 2015).
The effects of testosterone replacement therapy (TRT) on the immune system have not been looked into, but it has a positive effect on elderly men (Osterberg, Bernie, and Ramasamy, 2014). However, Braude, Tang-Martinez, and Taylor (1999) challenge the wisdom that testosterone is an immuno-depressor. This is Jones’ only claim that is not outright wrong; there is data out there for both positions (of course I think that Braude, Tang-Martinez and Taylor, 1999 drive a solid argument against the testosterone-causes-immuno-suppression hypothesis).
The Jones says one of the dumbest things I’ve ever heard “And men, of course, are murdered much more than women. And who murders them—of course—other men. … Men murder at a much higher rate than women. … And that effect is striking—that effect is true worldwide—all over the world men, testosterone, murder at 10 times the rate of women. … So it’s a universal, it’s a biological universal, it’s clearly due to testosterone. There’s no question. The evidence is absolutely clear. So it’s a genetic phenomenon, it’s a gene for crime.” Should I be nice here and assume that whatever ‘gene’ he’s proposing that ’causes’ testosterone production actually causes the crime? Or should I take what he said at face value—that testosterone is a literal gene that causes crime? I think I’ll go with the second one.
“It’s certainly genetic, it’s also environmental. And you can’t disentangle it. You can change part of it—the environment—you can’t change the other part—the genes. And I always find it kind of odd that the public is so interested in the bit you can’t change—the genes—and is so uninterested in the bit you can—the environment.” This is wrong. Not all of it, but most of it. I don’t think that people are more interested in genes and toss aside environment—especially for testosterone. Because, as I documented yesterday, hereditarians assume that since testosterone has a heritability of around .6 then it must be mostly genetic in nature. This is wrong. As Jones said, the environment effects testosterone production too (though he didn’t go into the mechanisms).
The Left goes to the environment side—change the environment, change hormone production (this is true)—whereas the Right goes to the genes side—can’t change genes and environment is a product of genes so nothing can be done. (Oversimplified, don’t crucify me.) Both are wrong. Strong genetic determinism (gene G almost always leads to the development of trait T. (G increases the probability of T and the probability of T, given G, is 95% or greater) doesn’t make sense because a large majority of traits are moderately or weakly determined by genetics (Resnick and Vorhaus, 2006).
In sum, Jones is clueless about testosterone. He only really said one thing that is not outright wrong (but it is questionable). It doesn’t cause crime, it doesn’t cause men to murder more. The press has gotten all of these views into people’s heads because they want to demonize men—and the hormone that is largely responsible for male-ness. It’s incredible that this guy is both a geneticist, science writer and professor of genetics and still calls testosterone a ‘gene’ saying that it is responsible for ‘most of the crime’ committed. Anyone who has been reading this blog for the past year or so since I have began revising many of my main views knows how wrong this is. People really need to get a clue on testosterone and stop spreading bullshit. I know that I’ll have to keep correcting misconceptions on testosterone for a good long time (like with r/K theory) but I enjoy writing about both things so it’s not too big a deal. I just wish people would actually educated themselves on basic physiology so that the trainwreck of a video that Jones made does not get made.
No, Black Women Do Not Have Higher Testosterone than White Women (And More On Hereditarian Claims on Racial Testosterone Differences)
It has been over a year since I wrote the article Black Women and Testosterone, and I really regret it. Yes, I did believe that black women had higher levels of testosterone than white women due to one flimsy study and another article on pregnant black women. I then wised up to the truth about testosterone and aggression/crime/race/sex and revised the articles (like I have done with r/K selection theory). However, after I revised my views on the supposed differences in testosterone between black men/white men and black women/white women, people still cite the article, disregarding the disclaimer at the top of the article. I quoted Mazur (2016), who writes (emphasis mine):
The pattern [high testosterone] is not seen among teenage boys or among females.
There is no indication of inordinately high T among young black women with low education.
Honor cultures are cast as male affairs, but with T data in hand for both sexes, it is worth exploring whether or not a similar pattern exists among women. Mean T was calculated as a function of age for the four combinations of race and education used in Table 1 but now for women. All plots show T declining with age, from about 35 ng/dL in the 20–29 age group to about 20 ng/dL among women 60 years and older. The four plots essentially overlap without discernible differences among them. Given the high skew of T among adult females, both raw and ln-transformed values were analyzed with similar results. There is no indication of inordinately high T among young black women with low education.
In the present study, at least, the sexes differ because the very high T seen among young black men with low education does not occur among young black women with low education.
This is very clear… Mazur (2016) analyzed the NHANES 2011-2012 data and this is what he found. I understand that most HBD bloggers do believe this, well, like a lot of their strong assertions (which I have rebutted myself), they’re wrong. They don’t get it. They do not understand the hormone.
The reason why I’m finally writing this (which is long overdue) is that I saw a referral from this website today: https://www.minds.com/RedPillTV who writes about the aforementioned black women and testosterone article:
It is known that blacks have the highest levels of testosterone out of the major races of humanity. However, what’s not known is that black women have higher rates than white women. The same evolutionary factors that make it possible for black men to have high testosterone make it possible for women as well.
…..No. It seems that people just scroll on by the disclaimer at the top that is bolded and italicized and just go to the (now defunct) article and attempt to prove their assertion that black women have higher testosterone than white women with an article that I have stated myself I no longer believe and have provided the rationale/data for the position. This shows that people have their own biases and no matter what the author writes about their views that have changed due to good arguments/data, they will still attempt to use the article to prove their assertion.
I’ve written at length that testosterone does not cause 1) aggression, 2) crime and 3) prostate cancer. People are scared of testosterone mostly due to the media fervor of any story that may have a hint of ‘toxic masculinity’. They (most alt-righters) are scared of it because of Lynn/Rushton/Templer/Kanazawa bullshit on the hormone. Richard Lynn doesn’t know what he’s talking about on testosterone. No, Europeans did not need lower levels of aggression in the cold; Africans didn’t need higher levels of aggression (relative to Europeans) to survive in the tropics. The theory that supposed differential testosterone differences between the races are “the physiological basis in males of the racial differences in sexual drive which form the core of the different r/K reproduction strategies documented by J.P. Rushton” (Lynn, 1990: 1203). The races, on average, do not differ in testosterone as I have extensively documented. So hereditarians like Lynn and others need to look for other reasons to explain blacks’ higher rate of sexual activity.
Rushton’s views on the testosterone and supposed r/K continuum have been summarily rebutted by me. These psychologists’ views on the hormone (that they don’t understand the production of nor do they understand the true reality of the differences between the races) are why people are afraid of testosterone. No, testosterone is not some ‘master switch’ as Rushton (1999) asserts. Rushton asserts that racial differences in temperament are mediated by the hormone testosterone. He further dives into this assertion stating “Testosterone level correlates with temperament, self-concept, aggression, altruism, crime, and sexuality, in women as well as in men (Harris, Rushton, Hampson, & Jackson, 1996). It may ‘correlate’ with aggression and crime, but as I have documented, they do not cause either.
The aggression/testosterone correlation is only .08 (Archer, Graham-Kevan, and Davies, 2005). Furthermore, the diurnal variation in testosterone does not directly correlate to when testosterone levels are highest in the day (at 8 am and drop thereafter), with adults peaking in crime at 10 pm and kids at 3 pm, with rises at 8 pm and 12 pm (not surprisingly, kids go in to school around 8 am, go to recess at 12 and leave at 3).
If you’ve read as much Rushton as I have, you’ll notice that he begins to sound like a broken record when talking about certain things. One of the most telling is Rushton’s repeated assertions that blacks average 3-19 percent higher testosterone than whites. The 3 percent number comes from Ellis and Nyborg (1992) and the 19 percent number comes from Ross et al (1986) (which Rushton should know that after adjustments for confounding, it decreased to 13 percent). These are the only studies that hereditarians ever cite for these claims that blacks average higher testosterone than whites. That seems a bit fishy to me. Cite a 30-year-old study along with a 25-year-old study (with such huge variation from Rushton and those who cite him for this matter—3-19 percent!!) as ‘proof’ that blacks average such higher levels of testosterone in comparison to whites.
Ross et al (1986) is one of the most important studies to rebut for this hereditarian claim that testosterone causes all of these maladies in black American populations. Ross et al (1986) propose that higher levels of the hormone lead to the higher rates of prostate cancer in black American populations. However, meta-analyses do not show this (Zagars et al, 1998; Sridhar et al, 2010).
Rushton et al’s assertions—largely—lie on this supposed testosterone difference between the races and how it supposedly leads to higher rates of crime, prostate cancer, aggression, and violence. However, the truth of the matter is, this is all just hereditarian bullshit. Larger analyses—as I have extensively documented—do not show this trend. And even accepting the claim that blacks have, say, 19 percent higher levels of testosterone than whites, it still would not explain the supposed prostate cancer rates between the races (Stattin et al, 2003; Michaud, Billups, and Partin, 2015). Even if blacks had 19 percent higher testosterone than whites, it would not explain higher levels of crime nor aggression due to such a hilariously low correlation of .08 (Archer, Graham-Kevan, and Davies, 2005).
Finally, I have a few words for Michael Hart and his (albeit sparse) claims on testosterone in his 2007 book Understanding Human History.
Hart (2007) writes:
(Many of these differences in sexual behavior may be a consequence of the fact that
blacks, on average, have higher levels of testosterone than whites.7) (pg. 127)
And….. footnote number 7 is…. surprisingly (not): 7) Ross, R., et al. (1986). Not going to waste my time on this one, again. I’ve pointed out numerous flaws in the study. (I will eventually review the whole thing.)
It seems unlikely, though, that the higher testosterone level in blacks — which is largely genetic in origin — has no effect on their sexual behavior (pg. 128; emphasis mine)
This is bullshit. People see the moderately high heritability of testosterone (.60; Harris, Vernon, and Boomsma, 1998) and jump right to the “It’s genetics!!!” canard without even understanding its production in the body (it is a cholesterol-based hormone which is indirectly controlled by DNA, there are no ‘genes for’ testosterone). Here are the steps: 1) DNA codes for mRNA; 2) mRNA codes for the synthesis of an enzyme in the cytoplasm; 3) luteinizing hormone stimulates the production of another messenger in the cell when testosterone is needed; 4) this second messenger activates the enzyme; 5) the enzyme then converts cholesterol to testosterone
I have documented numerous lines of evidence showing that testosterone is extremely sensitive to environmental factors (Mazur and Booth, 1998; Mazur, 2016), and due to the homeodynamic physiology we have acquired due to ever-changing environments (Richardson, 2017), this allows our hormones to up- or down-regulate depending on what occurs in the environment. The quote from Hart is bullshit; he doesn’t know what he’s talking about.
For females in Siberia, the disadvantages of failing to find a man who would
provide for her and her children during their childhood were much greater than they were in tropical climates, and females who were not careful to do so were much less likely to pass on their genes. Furthermore, because females in harsh climates were so demanding on this point, males who seemed unlikely to provide the needed assistance found it hard to find mates. In other words, there was a marked sexual selection against such males. Such selection could result, for example, in the peoples living in northerly climates gradually evolving lower levels of testosterone than the peoples living in subSaharan Africa. (pg. 131)
This is a bullshit just-so story. Africans in Africa have lower levels of testosterone than Western men (Campbell, O’Rourke, and Lipson, 2003; Lucas and Campbell, and Ellison, 2004; Campbell, Gray, and Ellison, 2006).
Note also that a difference in testosterone level frequently affects not
only the sexual behavior of a young male, but also his aggressiveness.
No it does not (Archer, Graham-Kevan, and Davies, 2005).
Thankfully, that’s all he wrote about testosterone. There is so much bullshit out there. Though, people who like and seek out the truth will learn that there are no racial differences and that testosterone does not cause crime/aggression/prostate cancer and that it’s just hereditarian bullshit.
The evidence I have amassed and the arguments I have given point to a few things: 1) the races do not differ in testosterone/there is a small negligible difference; 2) testosterone does not cause crime; 3) testosterone does not cause aggression; 4) black women do not have higher levels of testosterone than white women; 5) high levels of testosterone do not cause prostate cancer; and 6) even allowing a 19 percent black/white difference will not have hereditarian claims hold true.
So for anyone who comes across my old articles on testosterone and sex/race, do a bit more reading of my newer material here to see my new viewpoints/arguments. DO NOT cite these articles as proof for your claims of higher levels of black men/women. DO cite the old articles ALONG WITH the new ones to show how and why my views changed along with the studies I have cited that changed my view. (Actually understanding the production of testosterone in the body was a huge factor too, which I talk about in Why Testosterone Does Not Cause Crime.)
Job performance is supposedly one measure that validates the construct of IQ tests since they correlate so highly with IQ tests (Schmidt et al, 1986). However, there are problems with the methods used to get the high correlations (sometimes doubling correlations, there are also questions to the robusticity of the studies meta-analyzed); corrections used have to make a number of assumptions; uncertainty of the interpretation of what the supposed IQ and job performance correlations mean; other non-cognitive factors may also explain differences in job performance. Most surprisingly, intelligence test scores did not predict promotion to senior doctor and intelligence does not predict careers.
Job performance and IQ
Does IQ really correlate around .5 with job performance like is so commonly stated? There are a number of problems citing such the commonly used meta-analyses for evidence that IQ does indeed predict job performance.
Richardson and Norgate (2015) show that one should use caution when interpreting the results of IQ and job performance on the basis of numerous criteria. It is important to note that job performance is rated by supervisors, which is, of course, a problem since supervisors tend to be subjective in their ratings. Further, supervisor ratings have low correlations with work performance, while work knowledge has a correlation of around .3 (Richardson and Norgate 2015; Richardson, 2002). So, one of the main things that the correlation hinges upon is strongly subjective.
However, one of the most important things to note here is that the validation of IQ tests is relied on with correlations with other tests. For instance, blood alcohol and level of consumption are valid constructs. The higher your blood alcohol is, the more alcohol you consumed. There is no such validity for the construct of IQ—except correlations with other tests—which is a huge problem. This goes back to the fact that there is no individual theory of intelligence differences (Deary, 2001: 14) and no neurophysiological theory of g (Jensen, 1998: 257).
So IQ tests don’t have the same construct validity that other models that describe biologic/physiologic functions do; hundreds of studies before the 70s showed low correlations between IQ and job performance; corrections for error make a lot of assumptions; the common claim that the IQ/job performance correlation increases with more complex jobs is not observed in more recent studies; and there is great uncertainty in the interpretation of the IQ and job performance correlation, due to the fact that there is no construct validity to IQ tests. This goes back to the question: What is it that IQ tests test (Richardson, 2002)? Is it the ever-elusive general factor of intelligence? I’m skeptical there.
Richardson (2017) writes:
The committee described the differences as “puzzling and somewhat worrisome.” But they noted how the quality of the data might explain it. For example, the 264 newer studies have much greater numbers of participants, on average (146 versus 75). It was shown how the larger samples produced much lower sampling error and less range restriction, also requiring less correction (with much less possibility of a false boost to observed correlations). And there was no need to devise estimates to cover for missing data. So, even by 1989, these more recent results are indicative of the unreliability of those usually cited. But it is the earlier test results that are still being cited by IQ testers. (pg. 89)
IQ and job performance correlations are also substantially weaker in other parts of the world, such as the Middle East and China, where motivation and effort explain school and work performance and not cognitive ability (Byington and Felps, 2010). So, again, caution is to be taken when interpreting any IQ and job performance correlation, as well as—most importantly—asserting that higher IQ means better job performance.
In his 2015 book Intelligence in the Flesh, Guy Claxton wrote:
We saw earlier that Google is not impressed by people’s track records of success, but is equally sceptical of high IQs. Laszlo Bock, the senior vice-president in charge of ‘people operations’ – the head of HR – says: ‘For every job the No. 1 thing we look for is general cognitive ability, and it’s not I.Q. It’s learning agility. It’s the ability to process on the fly.‘ Behind the ability to learn quickly lies what Bock calls ‘intellectual humility.’ You have to be able to give up the knowledge and expertise you thought would see you through, and look with fresh eyes. People with a high IQ ofen have a hard time doing that. They are certainly no better than average at tolerating uncertainty or being able to adopt fresh perspectives.
Now that we know to take caution when speaking about the IQ and job performance correlation, what do IQ tests say about success as a doctor?
Doctors and IQ
Since becoming a doctor is so demanding and takes a lot of time and motivation to complete a doctoral degree, most rightly assume that it takes a higher than average intelligence to acquire these accolades and become a medical doctor. However, reality is more nuanced.
McManus et al (2003) put forth three hypotheses: 1) the achievement argument: A-levels ensure maximum competence on sciences which are basic to medicine (biology and chemistry); 2) the ability argument: Academic success depends mainly on cognitive ability; and 3) the motivation argument: Using A-levels is effective because it University education not only reflects intelligence but motivation and good, consistent study skills.
There is evidence that IQ is irrelevant to becoming a doctor and that it did not predict dropping out of the program, career outcome, amount of research publications published, or stress, burnout and satisfaction with taking a career in medicine (McManus et al, 2003). Diplomas, higher academic degrees, and research publications were significantly correlated with personality.
McManus et al (2003) write:
Intelligence did not independently predict dropping off the register, career outcome, or other measures.
Intelligence does not predict careers, thus rejecting the ability argument. A levels predict because they assess achievement, and the structural model shows how past achievements predict future achievement.
And on the causes for dropping out:
All 511 students registered with the General Medical Council, but only 464 were on the 2001 Medical Register. The 47 doctors who left the register (a mean of 11.1 years after qualifying; SD 5.9; range 2-23) had lower A level grades but not lower AH5 scores (table A, bmj.com); see http://www.bmj.com for ROC analysis. Two doctors subsequently returned to the register. Of the remainder, three had died, contact details were available for 35, and no information was available for seven.
So lower intelligence scores were not the cause for dropping out.
McManus et al (2003), however, could not distinguish between the motivation and achievement argument, but falsified the intelligence argument (Hypothesis 2 was falsified, but not 1 and 3).
This was also replicated by McManus et al (2013), where they should that IQ scores did not predict promotion to senior doctor. A-level scores, yet again, predicted success better when it came to doctoral success.
The relationship between IQ and job performance is not as clear-cut as most would like to believe. One of the most important factors there, in my opinion, is the subjectivity of supervisors on the performance of their workers. Numerous factors could influence a supervisors’ view of an individual, biasing the supervisor to a high rating. Furthermore, the corrected correlations are a problem. More recent analyses show a correlation of .25 (Richardson, 2017: 89).
Perhaps more importantly, two studies show that there is no predictive effect on job performance when it comes to IQ for doctors (McManus et al, 2003; McManus et al, 2013). They show that A-level scores predict success better, with personality variables mediating other relationships—not IQ scores.
The fact of the matter is, job performance and IQ is on shaky ground since IQ tests are not constructed valid, and the job performance ratings are based on supervisor ratings which are highly subjective. Analyses in other locations around the world show that IQ does not predict job performance, however, motivation and effort do. IQ does not predict a doctor’s job performance; job performance tests do not prove the validity of IQ tests.
IQ does not predict a doctor’s job performance; job performance tests do not prove the validity of IQ tests.
[Edit: I have come across more data on doctors IQ. Some studies show that complaints by patients on their doctors are related to infractions. Perry and Crean (2005) show that the average IQ for a doctor is 125. They also state that neurocognitive impairment may be responsible for 63% of all physician related adverse events. This same observation is also noted in other studies (Pitkanen, Hurn, and Kopelman, 2008; Lauri et al, 2009; Kataria et al, 2014). Also of note is that these papers—to the best of my knowledge—do not explore the role of stress in cognitive decline. Though Pitkanen, Hurn, and Kopelman (2008) note that depression, PTSD, amnesia, transient global amnesia, alcoholic brain damage, frontotemporal dimentia, dimentia, alzheimer’s disease, vascular dimentia, and post-traumatic amnesia (PTA) influence cognitive decline in doctors.
Veena et al, (2015) show that 88 percent of medical students had near average intelligence, putting in 6 hours a day of studying, while 10 percent of students had above average IQ, spent less time studying but were sincere in their classes.
Veena et al (2015) conclude:
Students with near average IQ work hard in their studies and their academic performance was similar to students with higher IQ. So IQ can`t be made the basis for medical entrance; instead giving weight-age to secondary school results and limiting the number of attempts may shorten the time duration for entry and completion of MBBS degree.
So students with average intelligence work just as hard (if not harder) than people with above average IQ and have similar educational achievement. This shows that IQ can’t be the basis for medical school entry.
This is a really interesting matter and I will cover it more in the future. I’ve been wondering for years if there is data on physician/doctoral malpractice and race I have yet to come across any papers on the matter. If anyone knows of any, please leave some citations.]
The other day Anonymous Conservative (AC) published an article titled Criticism Of r/K Theory In The Comments. I’m not too worried about what he wrote in the main article (I may tackle that later if I feel up to it), but what I am worried about is someone’s critique of my article r/K Selection Theory: A Response to Anonymous Conservative. Since this guy uses AC’s writings who, of course, is influenced by Rushton’s application of r/K to humans, it shows that he’s pretty clueless about 1) the theory as a whole and 2) the theory’s ultimate status in biology. (Also check out Phil’s comments in the AC thread.)
The individual in question, one ‘Samuel Skinner’ calls my critique of AC “genuinely bad” and that he would “cover the most obvious mistakes“, well let’s take a look at my ‘genuinely bad‘ critique to AC.
RR: You don’t get it. Mongoloids being r-selected is straight from Rushton. He asserts that they have cold-adaptations. Cold adaptations are due to cold weather. Cold weather is an agent of r-selection (temperature extreme).
Samuel Skinner: Mongoloids have a variety of genetic adaptions to cold. If you drop one buck naked in the winter, they will still freeze to death. The actual adaption they have is wearing thick clothing covering the entire body, something that is both K and not existent in Africa. Needless to say knowing how to gather materials, make clothing and maintain it is a K selective pressure.
So “the actual adaptation they have” is to “wear thick clothing“? This is bullshit and you know it. I covered human physiological adaptations to the cold last month: Human Physiological Adaptations to Climate. Clothes weren’t made in Africa? “Knowing how to gather materials, make clothing and maintaining it” is not a “K selective pressure“.
RR: Endemic (native) disease is an agent of K-selection. Since the disease is constant, then the population under that agent of K-selection can prepare ahead for disease.
Samuel Skinner: That requires the preparation to actually work; if preparation has less effect on genetic pay offs then having children faster, having children faster wins.
The preparation does work. In the case of malaria (an endemic disease), one-fifth of patients use traditional malarial remedies in malaria-stricken countries (Wilcox and Bodecker, 2004).
Endemic and infectious disease is an agent of K-selection:
(From Anderson, 1991: 53)
RR: Do groups not work together in Africa to reach common goals? In the Pleistocene as well? Citations? Think before you write (and cite), because hunting bands in our species began with Homo erectus.
Samuel Skinner: NPC talks about clannishness and IQ difference in other posts. So he does believe that groups in Africa do not work together to reach common goals. I’m honestly not sure what he is thinking here.
Yes I do. But to say that ‘Africans don’t work together’ is stupid because Africa is a huge continent. Which African ethnies? Etc. And that’s also an incorrect claim.
RR: Density-dependent pressures are things such as endemic disease in Africa—which is necessary for a K-selected history since density-dependent natural selection occurs at or close to the environmental carrying capacity
Samuel Skinner: Yes, if a disease is transmitted through person to person contact and non-discriminatory. Malaria is transmitted through mosquitoes; the amount adding additional people increases its rate is negligible.
“This therefore provides empirical confirmation that sex ratio has an immediate impact on transmission success and that it is density-dependent” (Mitri et al, 2009). Endemic disease (like malaria) work in a density-dependent fashion (Anderson, 1991: 51).
Here is what people like Samuel Skinner and AC don’t get: r/K selection theory WAS discarded; it is no longer in use. Age-specific mortality better explains these trends than r/K selection (Reznick et al, 2002: 1518). I’ve also covered how the so-called ‘unidimensional construct’ or r on one end and K at another is wrong: “It appears that the original HKSS items are best represented as four distinct but related dimensions, and do not represent a unidimensional construct. This conclusion is reinforced by relationships between HKSS total scores and life history measures: The significant correlations that were found were contrary to the predictions made by the Differential K literature (Figueredo et al., 2013; Rushton, 1985). We found that high K scores were related to earlier sexual debut and unrelated to either pubertal onset or number of sexual partners. This suggests that the HKSS does not reflect an underlying “K dimension” (Copping, Campbell and Muncer, 2014).
It truly is tiring rebutting the same old bullshit arguments on r/K theory. I see AC’s bullshit on Twitter when I search ‘r/K Selection Theory’, but the individual who pushes the bullshit will not accept my invitation to come to this blog and discuss it with me.
The most important thing to know here is that the unidimensional construct that Pianka (1970) formulated is wrong. Joseph Graves (2002) reviews some of the literature on the theory, showing that Pianka’s (1970) verbal theory is wrong, and that r/K selection fell out of favor in the late 70s. It’s worth noting that Pianka gave NO experimental rationale (Graves, 2002: 135) to his unidimensional construct (which Copping, Campbell and Muncer, 2014). Do you see how this theory holds no weight in evolutionary biology anymore?
Here is what Reznick et al (2002) write:
Although life-history theory has shifted away from a focus on r- and K-selection, the themes of density-dependent regulation, resource availability, and environmental fluctuations are integral to current demographic theory and are potentially important in any natural system
I see the term density-dependent regulation, which I do not see on AC’s blog (the only thing that comes up if you search that term on his blog are the responses to me… that should tell you something). In regards to resource availability Reznick et al (2002: 1517) write: We have also found a potential role of resource availability, either as a consequence of environmental factors that are correlated with, but otherwise independent of predators, or as a consequence of indirect effects of predation (Reznick et al. 2001)”. If I were you I’d read some of the literature on this before writing more bullshit.
Skinner also writes: “Again, not following. The link between fertility and disease is pretty clear- after a die off the population rebounds. If a population is near carrying capacity and suffers a die off, the growth rate of the survivors increases.” Except African populations have had much more time to reach their environmental carrying capacity and to experience the K-selected agents of natural selection, like endemic disease (Anderson, 1991: 59).
Then AC jumps in and writes: “You cannot take a Biology 101 class without learning about r/K. It is in the textbooks, and it is seen as an excellent theory, akin to Newtonian Physics. Sure relativity and Quantum Mechanics came along and showed that Newtonian physics wasn’t the entire ball of wax. But you still learn Newtonian Physics, because it is fundamental to understanding everything else.” This, again, is bullshit. AC, have you taken a Bio 101 class? I took one. Not one mention of this discredited theory, I have an in use biology textbook (Understanding Biology, 2nd edition, Mason et al, 2017; check pages 905-908 in the textbook to verify this) and in the section on reproductive strategies (which is what r/K selection theory is, at its core) r/K selection is not mentioned once. Why make claims that you know you cannot verify?
AC: “What we are doing here is not something where you can point to a single old study, and say, here it all is, in one place. Bringing all this together is new, even if what is being brought together is well established.“
That doesn’t mean it’s right.
AC: The issue is, you have one area of study of humans (political science) where it is long established that humans spontaneously diverge into two groups, which the literature has recognized are so divergent that they call them Left and Right, as in each points in the opposite direction.
So stop dodging me and answer this question: Are liberals and conservatives local populations? If so, where did they evolve?
AC: “Now I know you didn’t read the book because you are hung up on the use of the phrase “r/K Theory.” In the book there is a chapter devoted to that. I use the meme of r/K Theory for the same reason it is taught in biology – it is a quick way to bring people up to speed on the purposes of these traits, and how they affect reproduction/survival under different conditions.”
Don’t worry; I’ll read your book soon enough and will probably have tons of material to rebut. Anyway, using discredited bio theories isn’t a good way to push something.
AC: “If it is done right, this will ultimately be a massive field of study with thousands of biologists and political scientists taking it apart and trying to figure how aggressive stimuli affect people’s r/K traits, vs sexual stimuli, vs pleasureable things like food, vs quick blips of K followed by long periods of r, vs long constant K, vs disease mortality that is totally random, and on and on.”
You have some strange dreams. It won’t happen. Individuals WITHIN A SPECIES are not R OR K. R AND K ARE NOT ADJECTIVES (Anderson, 1991: 57).
AC: “On Rushton, unless he ever mentioned politics (he didn’t),“
AC: “You have married black conservatives and married white conservatives and married Asian conservatives. They all have more in common psychologically than the leftists of their fellow races. Mixing them along racial lines only muddies the waters, and hides that all races have been exposed to harshness and ease, and have adapted the requisite psychologies to function and persist under either.“
No it doesn’t ‘muddy the waters’. I believe now you’ll point to black Trump supporters going against BLM or white Leftists going against their interests. SO WHAT. You can create any just-so story you’d like, you won’t be right.
Something AC doesn’t get is that using the discredited r/K continuum, conservatives would be r (lower IQ, more children; women who reported being religious stated that having children was more important to them; Hayford and Morgan, 2008) in comparison to liberals who would be K (fewer children, higher IQs). Of course, he just immediately states that cons are K and libs are r, since the verbal theory from Pianka (1970) had the ‘good traits’ on K and ‘bad traits’ on r. (Read r/K theory: Conservatives = r, liberals = K (reminder to the ignorant)). I’ve already covered that libs are more intelligent than cons (Kanazawa, 2010; Kanazawa, 2014), and that conservative countries have lower IQs (and are non-white and third world) in comparison to liberal countries (which are majority white…). Conservatives are more likely to be religious (Morrison, Duncan, and Parton, 2015; McAdams et al, 2015), and religious people have lower IQs (Zuckerman, Silberman, and Hall, 2013; Ritchie, Gow, and Deary, 2014; Pennycook et al, 2016; Dutton and Linden, 2017). Intelligence is also associated with social and economic liberal views (Carl, 2014). Lastly, research into the psychology of continents shows that liberal continents are more intelligent than conservative continents (African countries conservative, European countries liberal… what’s that tell you?) (Stankov and Lee, 2016). So, using Rushton’s/Pianka’s continuum, who looks r and K now?
This, as usual, is the perfect example of implicit bias. My team is best and has the good traits, the other team is worse and has the bad traits. It’s dumb, it doesn’t make sense. AC will try to get ‘the truth’ about this theory out to people, well he has a foil in myself. I enjoy talking about this and debating it, but it seems like most people don’t understand the ecology behind the theory. They have their biases and will search for anything to confirm them. That’s not science.
Stop pushing r/K theory. It’s long dead. Just because some non-specialist idealogue pushes something and warps studies to fit his views while ignoring contrary evidence, DOES NOT mean that the theory is ‘back’ in style or anything to that effect. One biased person picked up the dead body of the (discredited) r/K continuum and attempted to revive it. Well I’ve shot it back down. It’s dead. Let it rest in peace and stop attempting to revive it.
Also see my other articles on r/K Selection Theory
Also read: r/k selection political theory is rubbish
Much has been written about the genotypic and phenotypic differences in Jamaicans, Kenyans, and Ethiopians. Why do they dominate these competitions? Is it cultural? Genetic? Does training matter more? Grit? Expertise? There are multiple reasons that they have such an advantage, the most important one being their morphology/somatype. Of course other physiologic and morphologic factors come into play for these three populations, but the greatest physical advantage they have is their somatype which lends itself to running—whether short, medium or long distance.
Back in July, I argued that the wide-hipped Neanderthals were stronger than the recently migrated Homo sapiens, due mostly to pelvic anatomy (along with Neanderthal protein intake). That’s one of the keys to explaining African dominance in running: their long slender bodies with high limb ratios.
Kenyans and Ethiopians
Kenyan distance running is driven by an ethny named the Kalenjin, particularly of the Nandi tribe. Much research has been undertaken on the physiology and morphology of certain subpopulations of Kenyans, with a complex genotype, phenotype, and even SES interaction driving the dominance of this subpopulation (Tucker, Onywera, and Santos-Concejero, 2015). Another important factor is their low BMI. Kenyans have the lowest BMIs in the world at 21.5, which considerably helps in regards to distance running (Radovanovic et al, 2014; Shete, Bute, and Deshmukh, 2014; Sedeaud et al, 2015).
Kenyans—like Jamaicans and Ethiopians—dominate these competitions due to a complex interaction between genes, environment and SES (Tucker, Onywera, and Santos-Concejero, 2015). Though, of course, a lot of what makes certain Kenyan populations dominate is trainable in other populations. Caucasians can have similar trainability in regards to Vo2 max, oxidative enzymes, and running economy. However, Kenyans are more likely to be slender with longer limbs which is a huge advantage in these competitions. So having a good running economy and a high Vo2 max may be the primary causal factors that cause them to be so good at distance running, with, as I’ve noted in the past, a higher genetic ceiling for high Vo2 max, along with high-altitude training (Larsen, 2003). Though Saltin et al (1995) conclude that physical activity during childhood combined with intense training as a teenager explains the higher Vo2 max in Kenyan boys. Other factors such as low blood lactate and ammonia accumulation are also important.
Genetics, though, is the most likely explanation for African distance-running dominance (Vancini et al, 2014; see Scott and Pitsiladis, 2007 for alternative view that as of yet there are no genetic evidence for African running superiority).
Not all studies show that Kenyans have more slow-twitch (type I) fibers than Caucasians, though the oxygen cost of running at a given velocity was found to be lower in elite Kenyan runners compared to non-Kenyans, which may be due to body dimensions. Apparently, there is no indication that Kenyans possess a pulmonary system that confers a physiologic advantage over non-Kenyans (Larsen and Sheel, 2015). Ethiopian diets, however, met the most recommendations for macronutrients, but fluids were lacking (Beis et al, 2011), similar to what is found on similar studies in Kenyans (Onywera et al, 2003).
It is important to note that not all of the literature out there says that there are mainly physiologic/genetic reasons for their success in distance running; other factors that may be at play are somatype which leads to exceptional biomechanical and metabolic efficiency, high-altitude training, and the want to succeed for economic and social advancement (Wilbur and Pitsiladis, 2012). Oxygen transport of the blood doesn’t explain Kenyan dominance either, they have similar oxygen transport as elite German runners (Prommer et al, 2010). Though, women and men from Ethiopia and Kenya, although they only account for <0.1% of the marathons and half-marathons, achieved the fastest times and were the youngest in the half-marathons and full-marathons (Knechtle et al, 2016). Similar results were seen in Switzerland, with male Africans being faster and younger than non-Africans (Aschmann et al, 2013).
From the years 2000-2014, Knechtle et al (2017) analyzed the Boston, Berlin, New York, and Chicago marathon along with the Stockholm marathon. Over this time period, Ethiopian men improved their times, but Ethiopian women didn’t. Age increased in Ethiopian men, but not women. Female and male marathon runners from Ethiopia were the fastest (Knechtle et al 2017). More studies, though, are needed to unravel the complex relationship between environmental and genetic factors that cause East Africans to dominate distance running (Onywera, 2009). However, elite endurance athletes consistently test higher than non-elite athletes on running economy, Vo2 max, and anaerobic threshold (Lorenz et al, 2013), and mechanical work may be able to predict recreational long distance performance (Tartaruga et al, 2013).
Jamaican sprinting dominance has been chalked up to numerous factors, most recently, symmetry of the knees and ankles (Trivers, Palestis, and Manning, 2013; Trivers et al, 2014). Trivers et al (2014) write in the Discussion:
Jamaicans are the elite sprinters of the world. Why? If symmetry of knees and ankles is a factor, why should Jamaicans be especially symmetrical (there is no knowledge of whether they actually are)? One possibility is heterozygosity for genes important to sprinting. The slave trade greatly increased heterozygosity on the West African side by mixing genes up and down the West coast of Africa from Senegal to Nigeria , . Recently a mtDNA haplotype has been isolated that correlates with success in African American–but not Jamaican–sprinters . Since there is a general (if often weak) positive relationship between heterozygosity and body symmetry  we are eager to do targeted studies of genomics on areas associated with sprinting, including energy substrate utilization, muscle fibre-type distribution and body composition analyses (with specific reference to the shape and size of the glutei maximi). Fast twitch (anaerobic) muscle fibres are characterized by specific adaptations which benefit the performances of explosive high-intensity actions such as those involved in sprinting. Notably, West Africans appear to have a higher fast twitch muscle fibre content than do comparable Europeans (67.5% vs 59% in one sample , as cited in ).
It’s interesting to note that the mtDNA haplotype predicts success in African American sprinters, but not Jamaicans. In regards to mtDNA haplotypes, Jamaican sprinters had statistically similar mtDNA haplotypes, which suggests that the elite sprinters arose from the same source population which indicates that there is no population stratification or isolation on sprint performance. African American sprinters and non-sprinters, on the other hand, had statistically significant differences in mtDNA, which implies that maternal ancestry plays a part in sprinting performance (Deason et al, 2011). Studying both maternal and paternal haplotypes to see where source populations originate is important in these fields, since if we know where their population came from, then we can better understand the hows and whys of elite running performance—especially between race. Though demographic studies on Jamaicans show that elite sprinters come from the same demographic population, so genetics cannot possibly account for Jamaican sprinting success, so their sprinting success may be related to environmental and social factors (Irving et al, 2013). We know little about the genomics of elite sporting performance (Pitsiladis et al, 2013), so the physical correlates (somatype) and physiologic correlates will do for now.
Usain Bolt is the current fastest man in the world, due in part to his anthropometric advantage (Krzystof and Mero, 2013). As everyone knows, you cannot teach speed (Lombardo and Deaner, 2014). Bolt himself has a large advantage, in part, to his power development and biomechanical efficiency compared to the people he competes with (Beneke and Taylor, 2010). Though one study has noted that a human may be able to run faster quadrupedally than bipedally–stating that at the 2048 Olympic Games, that the fastest human on the planet may well be a quadrupedal runner (Kinugasa and Usami, 2016). One of the most important factors of acceleration in the 100m sprint is stride frequency (Mackala, Fostiak, and Kowalski, 2015).
In Afro-Caribbean adolescents, body height and stride number to body height ratio were the main determinants of sprint performance (Copaver, Hertogh, and Hue, 2012). Body height being a predictor of sprint performance is nothing new; taller people have longer limbs; longer limbs cover more distance per step. Indeed, sprinters are taller than the American population, there is more variability in men than in women, sprinters have lower body mass and the height range excludes people who are really tall or really short (Uth, 2005).
I will touch on fiber typing again since I’ve come across new information on it.
East Asians are less likely to have the RR allele of the ‘sprint gene’ (MacArthur and North, 2004) (ACTN3) while Bantus are more likely to have it. Alpha-actinen-3 is a skeletal muscle isoform which is encoded by the ACTN3 gene. Alpha-actinen-3 deficiency is common in the general population (North, 2008; Berman and North, 2010), which means that most people in the general population are XX. Eighteen percent of the population on earth is homozygous for this mutation (Ivarsson and Westerblad, 2015). This allele is the 577X allele, and Bantus are less likely to have it while Eurasians are more likely to have it. The frequency of the RR genotype is also highest in Bantus than in Asians (Mills et al, 2001). This is one very important reason why Eurasians are not faster than Africans (somatype matters too, of course).
Elite sprinters are more likely to be RR and less likely to be XX. Why does this matter? It matters because the RR genotype with the right morphology, fiber type (fast twitch) and contractile properties of the individual fast twitch fibers contribute to heightened performance with an RR genotype (Broos et al, 2016). Jamaicans are also less likely to have the XX genotype (~2 percent) along with Kenyans (Scott et al, 2010). So this shows that since Jamaicans are less likely to be XX, they’re more likely to be RR. So since XX i negatively associated with sprint status, then populations that have a lower frequency will be more likely to have more sprinters, whereas a population that has the genotype will have fewer sprinters.
This is one of many genetic factors that account for elite sprinting performance between populations. So, clearly, the right muscle fiber type combined with the right genotype from the ACTN3 gene infers an advantage, contrary to Daniel MacArthur’s claims that it does not (one of the authors of numerous studies on the ACTN3 gene).
The genetics of sprinting/distance running is currently poorly understood. Though we have a few candidates (and they’re really good, showing variation where they should) like the RR ACTN3 genotype combined with fast twitch fibers. This is very important to note. If you’re missing this, and you’re short with a low Vo2 max and low limb length, there’s an extremely high chance you will not be an elite sprinter/distance runner. I cannot emphasize enough how much the physical factors mean when it comes to this.
It is possible that SES variables combined with other psycho-social factors could explain why these three populations excel so well in these sports. Though, on the other hand, you cannot discount that the individual has to have the right somatype and physical capabilities first. Contrary to popular belief, fiber typing DOES give an advantage, especially if combined with other variables. Low BMI is very important, as are long limbs and a taller than average height.
When it comes to Jamaicans, symmetry of the knees and ankles help considerably, along with a low body mass and taller body. SES factors could be driving the will to compete in these three populations, however, the physical ability needs to be there first, then it needs to be nurtured. Over the next 5 to 10 years, we will have a better understanding of why some populations excel over others and that will largely be due to somatype, physiology, and genetic factors, with SES and other psycho-social factors driving the want to excel in the sport.
The physical differences that underlie the success of these three populations needs more study. Elite athletes of Jamaican, Kenyan, and Ethiopian descent need to be studied more to untangle the physiologic, psychological, physical and social factors that have them excel so well. We know that certain combinations of traits infer a great advantage in certain populations, we now just need enough elite athletes of these populations to study to see how and why they excel so much. The current body of research reviewed here is a good start, though it does leave some questions unanswered.
Last month I argued that there was more to weight loss than CI/CO. One of the culprits is a virus called Ad-36. Obese people are more likely to have Ad-36 antibodies in comparison to lean people, which implies that they have/had the virus and could be a part of the underlying cause of obesity. However, a paper was recently published that your stool can predict whether or not you can lose weight. This is due to how certain bacteria in the gut respond to different macronutrients ingested into the body.
ScienceDaily published an article a few days ago titled Your stools reveal whether you can lose weight. In the article, they describe the diets of the cohort, which followed 31 people, some followed the New Nordic Diet (NND), while others followed the Average Danish Diet (ADD) (Hjorth et al, 2017; I can’t find this study!! I’ll definitely edit this article after I read the full paper when it is available). So 31 people ate the NDD for 26 weeks, and lost 3.5 kg (7.72 pounds for those of us who use freedom numbers) while those who ate the ADD lost an average of 1.7 kg (3.75 pounds for those of us who use freedom numbers). So there was a 1.8 kg difference in pounds lost between the two diets. Why?
Here’s the thing: when people were divided by their microbiota, those who had a higher proportion of Prevotella to Bacteriodoites lost 3.5 more kg (7.72 pounds) in 26 weeks when they ate the NND in comparison to the ADD. Those who had a lower proportion of Prevotella to Bacteriodoites lost no additional weight on the NND. Overall, they say, about 50 percent of the population would benefit from the NND, while the rest of the population should diet and exercise until new measures are found.
The New Danish Diet is composed of grains, fruits, and vegetables. The diet worked for one-half of the population, but not for the other. The researchers state that people should try other diets and to exercise for weight loss while they study other measures. This is important to note: the same diet did not induce weight loss in a population; the culprit here is the individual microbiome.
Now that those Bacteroidotes have come up again, this quote from Allana Collen’s 2014 book 10% Human: How Your Body’s Microbes Hold the Key to Health and Happiness:
But before we get too excited about the potential for a cure for obesity, we need to know how it all works. What are these microbes doing that make us fat? Just as before, the microbiotas in Turnbaugh’s obese mice contained more Firmicutes and fewer Bacteroidetes, and they somehow seemed to enable the mice to extract more energy from their food. This detail undermines one of the core tenets of the obesity equation. Counting ‘calories-in’ is not as simple as keeping track of what a person eats. More accurately, it is the energy content of what a person absorbs. Turnbaugh calculated that the mice with the obese microbiota were collecting 2 per cent more calories from their food. For every 100 calories the lean mice extracted, the obese mice squeezed out 102.
Not much, perhaps, but over the course of a year or more, it adds up. Let’s take a woman of average height. 5 foot 4 inches, who weights 62 kg (9st 11 lb) and a healthy Body Mass Index (BMI: weight (kg) /(height (m)^2) of 23.5. She consumes 2000 calories per day, but with an ‘obese’ microbiota, her extra 2 per cent calorie extraction adds 40 more calories each day. Without expending extra energy, those further 40 calories per day should translate, in theory at least, to a 1.9 kg weight gain over a year. In ten years, that’s 19 kg, taking her weight to 81 kg (12 st 11 lb) and her BMI to an obese 30.7. All because of just 2 percent extra calories extracted from her food by her gut bacteria.
This corresponds with the NND/ADD study on weight loss… This proves that there is more than the simplistic CI/CO to weight loss, and that an individual’s microbiome/physiology definitely does matter in regards to weight loss. Clearly, to understand the population-wide problem of obesity we must understand the intricate relationship between the microbiome/brain/gut/body relationship and how it interacts with what we eat. Because evidence is mounting that the individual’s microbiome houses the key to weight loss/gain.
Exercise does not induce weight loss. A brand new RCT (randomized controlled trial) showed that in a cohort of children who were made to do HIIT (high-intensity interval training) did show better cardiorespiratory fitness, but there were no concomitant reductions in adiposity and bio blood markers (Dias et al, 2017). What this tells me is that people should exercise for health and that ‘high’ that comes along with it; if people exercise for weight loss they will be highly disappointed. Note, I am NOT saying to not exericse, I’m only saying to not have any unrealistic expectations that cardio will induce it, it won’t!
Bjornara et al (2016) showed that, when the NND was compared to the ADD, there was better adherence to the NND when compared to the ADD. Poulskin et al (2015) showed that the NND provided higher satisfaction, and body weight reduction with higher compliance with the NND and with physical activity (I disagree there, see above).
This study is important for our understanding of weight loss for the population as a whole. More recent evidence has shown that our microbiome and body clock work together to ‘pack on the pounds‘. This recent study found that the microbiome “regulate[s] lipid (fat) uptake and storage by hacking into and changing the function of the circadian clocks in the cells that line the gut.” The individual microbiome could induce weight gain, especially when they consume a Western diet, which of course is full of fat and sugar. One of the most important things they noticed is that mice without a microbiome fared much better on a high-fat diet.
The microbiome ‘talks’ to the gut lining. Germ-free mice were genetically unable to make NFIL3 in the cell lining of the gut. So germ-free mice lack a microbiome and lower than average production of NFIL3, meaning they take up and store fewer lipids than those with a microbiome.
So the main point about this study is the circadian rhythm. The body’s circadian clock recognizes the day/night system, which of course are linked to feeding times, which turn the body’s metabolism on and off. Cells are not directly exposed to light, but they capture light cues from visual and nervous systems, which then regulates gene expression. The gut’s circadian clock then regulates the expression of NFIL3 and the lipid metabolic machinery which is controlled NFIL3. So this study shows how the microbiome interacts with and impacts metabolism. This could also, as the authors state, explain how and why people who work nights and have shift-work disorder and the concurrent metabolic syndromes that come along with it.
In regards to the microbiome and weight loss, it is poorly understood at the moment (Conlon and Bird, 2015), though a recent systematic review showed that restrictive diets and bariatric surgery “reduce microbial abundance and promote changes in microbial composition that could have long-term detrimental effects on the colon.” They further state that “prebiotics might restore a healthy microbiome and reduce body fat“(Segenfrado et al, 2017). Wolf and Lorenz (2012) show that using “good” probiotic bacteria may induce changes in the obese phenotype. Bik (2015) states that learning more about the microbiome, dysbiosis (Carding et al, 2015), and how the microbiome interacts with our metabolism, brain, and physiology, then we can better treat those with obesity due to the dysbiosis of the microbiome. Clark et al (2012) show how the mechanisms behind the microbiota and obesity.
Weight loss is, clearly, more than CI/CO, and once we understand other mechanisms of weight loss/gain/regulation then we can better treat people with these metabolic syndromes that weirdly are all linked to each other. Diets affect the diversity of the microbiome, the diversity of the microbiome already there though, may need other macro/micro splits in order to show differing weight loss, in the case of the NND and ADD study reviewed above. Changes in weight do change the diversity of the microbiome of an individual, however, the heritable component of the microbiome may mean that some people need to eat different foods compared to others who have a different microbiome. Over time, new studies will show how and why the macro/micronutrient content matters for weight loss/gain.
Clearly, reducing the complex physiological process of weight gain/loss to numbers and ignoring the physiological process and how the microbiome induces weight gain/loss and works together with our other body’s cells. As the science grows here we will have a much greater understanding of our body’s weight loss mechanisms. Once we do that, then we can better help people with this disease.
The debate on human potential—and whether or not it is innate and ‘in the genes’—is steeped in bias and ideology from both sides (despite the claims that HBD ‘has no ideological bias’). Hereditarians assume that human potential is ‘in the genes’, and some even believe that human potential is testable during embryonic development (like psychologist Stuart Ritchie). However, this assumes two things: 1) that genes are the masters of development, and not the slaves, and 2) that differences in potential are already encoded in the genes of the homunculus. I will show that these two assumptions are wrong.
Embryonic development is a part of a larger whole of a complex process. Cells, in the beginning of embryonic development, are totipotent—meaning they have the ability to become any type of cell (Condic, 2014) depending on what the intelligent system calls for. This is important to note: at the beginning, all cells are the same and, despite having the same genes, “they have the same potential to become any kind of differentiated cell for a particular organism” (Richardson, 2017: 156). It is also possible to grow stem cells in a lab that are pluripotent—which have the ability to become any cell in the body—called iPS cells.
Even embryos that are of low quality do end up developing into healthy babes (emphasis in second para mine):
Embryo quality as we see it under the microscope in the IVF lab gives us some reasonable ability to predict the chances for pregnancy after the embryo transfer procedure. However, because there are many other contributing factors involved that we can not see or measure, the generalizations about “quality” made from grading embryos are often inaccurate.
We see some cycles fail after transferring 3 perfect looking embryos, and we also see beautiful babies born after transferring only one “low grade” embryo. The true genetic potential of the embryo to continue normal development is very difficult to measure accurately unless we utilize preimplantation genetic screening (PGS) to select chromosomally normal embryos for transfer.
So it seems that not even just looking at the quality of the embryo will show you if it will grow into a healthy baby with no birth complications. Potential must come after the embryonic stage of development. Another thing about testing the ‘quality’ of the embryo: it tells nothing about “what is going on inside the embryo genetically“.
The thing is, most chromosomal and other defects in any embryos can be noted under a microscope within 3 days of the embryo forming. And if you paid attention to totipotent cells earlier, you’d know that those cells have the potential to become any cell in the body—which is driven by the body’s intelligent systems/cells.
So embryonic quality really has no bearing on whether or not the embryo will eventually reach birth. As I’ve argued before in Human Mating and Aggression—An Evolutionary Perspective, the age of the mother is one of the strongest predictors of whether or not there will be deleterious effects on the child—mostly after 35 years of age (O’Reilly-Green and Cohen, 1993; van Katwijk and Peeters, 1998; Stein and Susser, 2010; Lampinen, Vehviläinen-Julkunen, and Kankkunen, 2009, Jolly, 2010; Yaniv et al, 2010; Liu et al, 2011). However, there is evidence that a woman can be too young to become a mother (Geronimus, Korenman, and Hillemeier, 1994; Fall et al, 2015) and that children born to young mothers “might be better off if the parents waited a few years” (Myrskyla and Fenelon, 2012). The same holds true for fathers, with it recently being observed that older fathers and their offspring have lower evolutionary fitness even over across four centuries (Arslan et al, 2017). So it seems that the best predictor of embryonic quality is parental age (Scheffer et al, 2017)—not what an embryo really looks like or the totipotent cells already in the embryo.
So there is no test for the genetic potential of embryos and sperm—with the best tell being parental age. Embryonic development is a part of the intelligent developmental system and each stage of embryonic development is brand new, rather than being the cause of an already laid out blueprint. So even though the embryo has all of the same genes (in totipotent cells), they have the potential to become any cell in the body which is directed by the intelligent system (as noted above).
So if you understand embryonic development and how it’s a part of the intelligent system itself and not a part of an already laid out blueprint, then you’ll understand how potential—as we know it— is not in the embryo. They all have the same kinds of totipotent cells which have the chance to become any cell in the body which are then activated and used by the intelligent physiology. The age of both parents are the best predictors of embryonic quality—just by looking at the embryos after they’ve developed from blastocytes, you cannot infer that embryo’s potential.
Ken Richardson also responded to Stuart Ritchie’s article It’s now possible, in theory, to predict life success from a genetic test at birth to which Ken Richardson responded to. Potential is not in the embryo due to the number of totipotent cells in the embryo. Even ‘low-quality’ embryos can become healthy babes, so ’embryonic quality’ is not a good measure of whether or not it will be born with a defect, etc.