Sexual orientation – wired that way
In a recent post, I presented the evidence that sexual preference is strongly influenced by genetic variation (http://www.gnxp.com/wp/uncategorized/sexual-orientation-–-in-the-genes). Here, I discuss the neurobiological evidence that shows that the brains of homosexual men and women are wired differently from those of their heterosexual counterparts.
First, we must consider the differences between the brains of heterosexual males and females. These differences are extensive and arise mainly due to the influence of testosterone during a critical period of early development (see Wired for Sex). They include, not surprisingly, differences in the number of neurons in specific regions of the brain involved in reproductive or sexual behaviours as well as differences in the number of nerve fibres connecting these areas. But they also involve areas not dedicated to these types of behaviours, such as the cerebellum, for example, which is involved in motor control among other things, and which shows a very large difference between men and women. Another area that shows prominent differences is the corpus callosum, the very large sheet of fibres that connects the two cerebral hemispheres, which is larger in females, despite lower overall brain size. Indeed, females show greater and more efficient connectivity in cortical networks than males, on average.
Birth Months of World Cup Players
Four years ago I (and others) got in a dispute with Stephen Dubner and Steven Levitt (DL) about their claim that birth month had a meaningful impact on later success in professional sports because kids born in January were “old” for their age group and were, therefore, more likely to make elite travel, national teams for U-17 tournaments and the like. These athletes benefited from the better coaching and competition that they faced relative to the kids who were born later in the same calendar year but with the same natural ability. DL predicted that
If you were to examine the birth certificates of every soccer player in next month’s [2006] World Cup tournament, you would most likely find a noteworthy quirk: elite soccer players are more likely to have been born in the earlier months of the year than in the later months.
Words as alleles: A null-model for language evolution?
For me, recent computational accounts of language evolution provide a compelling rationale that cultural, as opposed to biological, evolution is fundamental in understanding the design features of language. The basis for this rests on the simple notion of language being not only a conveyor of cultural information, but also a socially learned and culturally transmitted system: that is, an individual’s linguistic knowledge is the result of observing the linguistic behaviour of others. Here, this well-attested process of language acquisition, often termed Iterated Learning, emphasises the effects of differential learnability on competing linguistic variants. Sounds, words and grammatical structures are therefore seen to be the products of selection and directed mutation. As you can see from the use of terms such as selection and mutation it’s clear we can draw many parallels between the literature on language evolution and analogous processes in biology. Indeed, Darwin himself noted such similarities in the Descent of Man. However, one aspect evolutionary linguists don’t seem to borrow is that of a null model. Is it possible that the changes we see in languages over time are just the products of processes analogous to genetic drift?
Authenticity and the Fermi paradox
I know that the simplest explanation for the Fermi paradox is that we’re the first intelligent technological life form in the universe. But thinking about Paul Bloom’s thesis that a sense of “authenticity” is necessary for pleasure made me wonder a bit more about the possibility that once intelligent life forms get to the point where they can “re-wire” themselves they see no need to interface with the real universe. Instead they would retreat into their own virtual reality domains where they could create their own cosmos, and also successively re-program themselves in terms of their goals to such an extent that their probability of ever wanting to extract themselves from the imagined world is zero. In other words, any sufficiently advanced life form will lack curiosity about the authentic world as we understand it.
Can linguistic features reveal time depths as deep as 50,000 years ago?
Throughout much of our history language was transitory, existing only briefly within its speech community. The invention of writing systems heralded a way of recording some of its recent history, but for the most part linguists lack the stone tools archaeologists use to explore the early history of ancient technological industries. The question of how far back we can trace the history of languages is therefore an immensely important, and highly difficult, one to answer. However, it’s not impossible. Like biologists, who use highly conserved genes to probe the deepest branches on the tree of life, some linguists argue that highly stable linguistic features hold the promise of tracing ancestral relations between the world’s languages.
Previous attempts using cognates to infer the relatedness between languages are generally limited to predictions within the last 6000-10,000 years. In the present study, Greenhill et al (2010) decided to examine more stable linguistic features than the lexicon, arguing:
The two cycles
I’m reading Brotherhood of Kings: How International Relations Shaped the Ancient Near East. The book basically outlines the international state system in the ancient Near East which fostered diplomatic relationships between the monarchies of the period. It is noted that this state system and diplomatic culture did not make it through the chaos which marks the transition between what we term the Bronze Age and Iron Age; the centuries between 1200 and 600 BC. I try and read about the ancient Near East when I can, it’s a hard area to find academic books accessible to lay people (I don’t know Sumerian or Akkadian for example, which means that a lot of the philological stuff goes over my head). But thanks the usage of cuneiform tablets which are often well preserved when palaces are burned down we have a substantial amount of records, albeit not of the personable narrative form excluding some exceptions (good for economic historians, not so much for cultural historians).
Psychometrics, epigenetics and economics
Two papers of interest. IQ in the Production Function: Evidence from Immigrant Earnings (ungated). And Human Intelligence and Polymorphisms in the DNA Methyltransferase Genes Involved in Epigenetic Marking. My impression is that the focus on epigenetics has a higher-order social motive; even the sort of humanists who are involved with N + 1 have asked me about the topic. But how many people know what methylation is?
Is the “missing heritability” right under our noses?
One of the major criticisms leveled against genome-wide association studies for complex diseases is that they have identified loci which account for a relatively small proportion of the variance in most traits. The difference between this small proportion of variance explained by known loci and the (generally large) total amount of variance known to be due to genetic factors has been called the “missing heritability”. Much ink has been spilled speculating about where this missing heritability lies.
Two papers published this week suggest that maybe much of the heritability isn’t actually missing at all. The argument is simple: when performing a genome-wide association study, people use very stringent thresholds for calling a SNP associated with a trait. This is reasonable; people generally want to follow up only on true positives. However, there are probably many loci which don’t reach these highly stringent cutoffs but which truly influence the trait in question. Using methods to determine how much of the variance can be explained by these loci of smaller effect, one group suggests that about half of the heritability of height can be explained by common SNPs, and possibly close to all of it if other factors are taken into account. The authors have, in their discussion, one of the most reasonable, non-hyperbolic discussions of where the “missing heritability” lies, and how whole-genome sequencing will affect genome-wide association studies. It’s worth reading the whole thing, but here’s their conclusion::
If other complex traits in humans, including common diseases, have genetic architecture similar to that of height, then our results imply that larger GWASs will be needed to find individual SNPs that are significantly associated with these traits, because the variance typically explained by each SNP is so small. Even then, some of the genetic variance of a trait will be undetected because the genotyped SNPs are not in perfect LD with the causal variants. Deep resequencing studies are likely to uncover more polymorphisms, including causal variants that will be represented on future genotyping arrays. Our data provide strong evidence that the variation contributed by many of these causal variants is likely to be small and that very large sample sizes will be required to show that their individual effects are statistically significant. A similar conclusion was drawn recently for schizophrenia. In some cases the small variance will be due to a large effect for a rare allele, but this will still require a large sample size to reach significance. Genome-wide approaches like those used in our study can advance understanding of the nature of complex-trait variation and can be exploited for selection programs in agriculture and individual risk prediction in humans.
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Citations:
Park et al. (2010) Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nature Genetics. doi:10.1038/ng.610.
Yang et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nature Genetics. doi:10.1038/ng.608.
The returns on homogeneity
A few days ago on Twitter I wondered if economists had calculated the costs of the world having a diversity of languages, instead of one language. The logic is that unintelligibility naturally throws up barriers to communication, and the flow of ideas and labor. This is one reason why the European Union necessarily has less labor mobility than the United States all things equal, the vast majority of Americans can understand each other to a very high level of clarity, while Europeans can attain this only within their nations. Even in societies where English is widely understood the level fluency variance and lack of uniform idiom may produce a suboptimal lingua franca across these English semi-fluent societies.
But Christopher Burd challenged me on this. He suggested that semi-permeability across cultures may actually be a feature, not a bug. As an example he offered the relative isolation of the Russian academic community, and so its insulation from the orthodoxies of English-speaking linguistics, allowed for the wider acceptance of heterodox models such as the Nostratic superfamily. I asked Burd if he was making an analogy to the shifting balance theory, and he stated that he was.
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“What has bioinformatics done for us”
So asks Anthony Goldbloom:
A British bioinformatician asks what bioinformatics has ever done for us? Or put differently, what is the single greatest biological discovery made possible by bioinformatics? He is offering $USD100 to the person who puts forward the most compelling answer (the prize is small but the idea is to stoke discussion). Kaggle would also welcome a guest post by the winner about their chosen discovery.
Answers should be in the form of a short abstract (200 words or less) in the comments section of this blog post. It would be helpful if participants could categorize the bioinformatics method (microarray analysis, sequence analysis, protein structure analysis, phylogenetic analysis…) as well as the application in biology (drug discovery, disease prevention, taxonomy, protein-protein interactions…). It is also preferable for answers to include an open source reference.
The winner will be selected by a panel of judges based on the significance of the discovery. We encourage everybody to give feedback using the “like” voting buttons.
You can enter as many ideas as you like – just get them in by Friday July 30th. Please include an active email address so that we can get in contact if you win.
I’ve closed comments. Leave them there.
The Times on the human genome at 10
Two articles in the New York Times this week revisit the promises made 10 years ago about how the sequencing of the human genome would revolutionize medicine (and how, obviously, it has not). There are things to quibble about–I could go on again about how some of the arguments against genome-wide association studies are silly, but hey, if silly arguments get published by prestigious people in prestigious journals, then I can hardly fault the Times for repeating them–but by and large the articles are spot on. The sequencing of the human genome has absolutely revolutionized biology, but that fact has had little impact on medicine to date.
There are reasons for optimism though. The most important reason is a bit of historical perspective–the road from identifying a gene involved in a disease to a treatment for that disease is…rocky, to say the least. The genetic cause of a particular type of cancer (CML) was discovered in 1960, but a treatment was approved by the FDA in 2001. For those keeping track, that’s 41 years. The gene for cystic fibrosis was discovered in 1988; drugs for that disease are finally in clinical trials now (and so will take at least 22 years to hit the market). Most drugs take well more than a decade to go through the regulatory pipeline. So even if associations between genes and common diseases had been discovered the day the genome was published (obviously, it took half a decade to even get those associations), the drugs inspired by those findings would still not be out. This quote is particularly relevant:
“I don’t think any of us in the business believed it would be a cornucopia,” said Frank L. Douglas, the former head of research and development at the drug company Aventis. “What we did believe, however, was that it would get easier. We forgot our history.”
And once again, life imitates The Onion.
Bad to the bone; the genes and brains of psychopaths
The manipulative con-man. The guy who lies to your face, even when he doesn’t have to. The child who tortures animals. The cold-blooded killer. Psychopaths are characterised by an absence of empathy and poor impulse control, with a total lack of conscience. About 1% of the total population can be defined as psychopaths, according to a detailed psychological profile checklist. They tend to be egocentric, callous, manipulative, deceptive, superficial, irresponsible and parasitic, even predatory. The majority of psychopaths are not violent and many do very well in jobs where their personality traits are advantageous and their social tendencies tolerated. However, some have a predisposition to calculated, “instrumental” violence; violence that is cold-blooded, planned and goal-directed. Psychopaths are vastly over-represented among criminals; it is estimated they make up about 20% of the inmates of most prisons. They commit over half of all violent crimes and are 3-4 times more likely to re-offend. They are almost entirely refractory to rehabilitation. These are not nice people.
So how did they get that way? Is it an innate biological condition, a result of social experience, or an interaction between these factors? Longitudinal studies have shown that the personality traits associated with psychopathy are highly stable over time. Early warning signs including “callous-unemotional traits” and antisocial behaviour can be identified in childhood and are highly predictive of future psychopathy. Large-scale twin studies have shown that these traits are highly heritable – identical twins, who share 100% of their genes, are much more similar to each other in this trait than fraternal twins, who share only 50% of their genes. In one study, over 80% of the variation in the callous-unemotional trait across the population was due to genetic differences. In contrast, the effect of a shared family environment was almost nil. Psychopathy seems to be a lifelong trait, or combination of traits, which are heavily influenced by genes and hardly at all by social upbringing.
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Population size predicts technological complexity in Oceania
Here is a far-reaching and crucially relevant question for those of us seeking to understand the evolution of culture: Is there any relationship between population size and tool kit diversity or complexity? This question is important because, if met with an affirmative answer, then the emergence of modern human culture may be explained by changes in population size, rather than a species-wide cognitive explosion. Some attempts at an answer have led to models which make certain predictions about what we expect to see when populations vary. For instance, Shennan (2001) argues that in smaller populations, the number of people adopting a particular cultural variant is more likely to be affected by sampling variation. So in larger populations, learners potentially have access to a greater number of experts, which means adaptive variants are less likely to be lost by chance (Henrich, 2004).
Models aside, and existing empirical evidence is limited with the results being mixed. I previously mentioned the gradual loss of complexity in Tasmanian tool kits after the population was isolated from mainland Australia. Elsewhere, Golden (2006) highlighted the case of isolated Polar Inuit, who lost kayaks, the bow and arrow and other technologies when their knowledgeable experts were wiped out during a plague.Yet two systematic studies (Collard et al., 2005; Read, 2008) of the Inuit case found no evidence for population size being a predictor of technological complexity.
Jews and genetics
Over at Discover Blogs I have a very long post up on Jews & Genetics. In particular the recent paper in AJHG. One observation I have to make about Jewish genetics: when it comes to PCA plots which illustrate the relationship of Jews, in particular Ashkenazi Jews, to other populations I’ve noticed that two different individuals can look at the same plot and reach diametrically opposite conclusions. For example, “this plot shows that Jews are European” vs. “this plot shows that Jews are not European,” where “this plot” refers to the same plot. An interesting illustration of the importance of interpretative frames when it comes to distilling the valid inferences from results.
Sexual orientation – in the genes?
Mirrored from http://wiringthebrain.blogspot.com
Is homosexuality a lifestyle choice or an innate biological disposition? The idea that it is a choice is certainly widespread – a part of several mainstream religious doctrines and political ideologies – and is used to condone significant discrimination against homosexuals and the criminalization of homosexual behaviour. But what does the science say?
The broad conclusions are that sexual orientation is an innate disposition – no different from whether you are left or right-handed – that it is affected by genetic influences and that it reflects differences in brain structure and function. I will consider the evidence of genetic effects on sexual orientation here, including some recent additions – a later blog will look at the neurobiological findings.
A number of family and twin studies of the heritability of sexual orientation, starting in the 1950’s, found significant genetic influences: the statistical likelihood of an individual being homosexual increased somewhat if they had a homosexual dizygotic (fraternal) twin and dramatically if they had a homosexual monozygotic (identical) twin. However, these studies have generally suffered from some methodological limitations, including small sample sizes, the possibility of ascertainment bias due to the methods of recruitment of participants and an assumption that homosexuality in males and females is likely caused by the same mechanisms.
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