genetics of normal variation

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Daniel,
Hmmmm. This will be the quandry for 10 years, 20 max. Time to dig into EnSembl and Zebrafish.....hmmm, conserved region....hmmmm ok, maybe that's bad.....hmmm, what's your cholesterol?

-Steve

Wow, I had no idea we were that far along in this. I figured all the stuff about certain health risks being genetically conditioned was simply based on large-scale studies, not knowledge of the actual specific genes involved. Seems like we'll live to see the day when newborn kids can get some serious medical-prediction stuff (if I'm not mistaken). Neat!

It's an interesting paper. Whole genome sequencing will be interesting for many reasons (particularly I think for human migration history) but it will be the variation scans that will be clinicaly useful whether for SNPs, indels, CNVs etc. Technology is steaming ahead but the biology can't move so quickly. Over 5 years of GWAS we have gone from a few $million per genome to a few $thousand but have not YET made much dent in gene based disease prediction (and I don't believe - re MCK - that 5 years of deep sequencing rare SNP search will be the answer either) - so you're final paragraph is spot on

I agree! I seriously doubt we will garner much more information about disease risk from genome sequencing than from GWAS studies. Until we have a better understanding of all the epigenetic and other genetic mechanisms (which are likely influenced by environmental exposures) which affect gene expression/translation etc over time, I suspect we will only be making little baby steps in finding specific factors involved in causing high disease risk. Great summary!

bring it on !

I'll bet you he has a malaria susceptability gene and if you treated him for lymes disease with doxycyline. He would get fat and have a heart attack from chronic babesiosis. Wilson and Chowning saw this in the Bitter Root Valley in 1905 ---- human piroplasmosis. They got run out of town and the cattle got treated. Good history --real history. Allergy and Immunology? No -- people dying from endemic disease. They saw a tick borne version of malaria back in 05 that still hasn't gotten proper recognition today. Babesia Microti, WA-1, MO-1, CA-1 --- we have very specific tests for those today --- but to convince your gatekeeper to look? You'll get thorazine before doxy. and guess what the nobel prize in medicine was awarded for in 1927? Creating thorazine to treat people with malaria and syphylis.

Thank God for Zyrtec!

I see about 5 patients per week who do not know at least half of their family history. Genetic testing TODAY is cost effective for them; in the future, it will be ILLEGAL not to.

I'm tired of the nay-sayers who want to live in the past: genetic testing is here to stay. Period.

And yes, the marginal utility of a WGS does not merit the massive increase in cost relative to a SNP chip. But that is always subject to revision as the cost curve progresses.

Hi Daniel,

Any comment on the MS twin study published in Nature?

@Steve "....hmmm, what's your cholesterol?"

What Steve advocates is an "occam's razor" of clinical application.

A genetic risk factor is not relevant when the factor itself can be directly tested. For example, if a patient complains of hypertension-like symptoms, you confirm a diagnosis with a sphygmomanometer, and then you treat the hypertension. A genetic test for a risk of hypertension would be redundant as the probability that the patient has hypertension is already "1.0".

However, if the genetic test informed us at some higher resolution about some malfunctioning biochemical pathway which caused the hypertension symptoms, and that information was necessary in some optimal clinical decision ---that would be useful. I'm not aware of any such application in this case.

People hope that DNA will have all the answers to good health. The problem is that those answers are not well translated into the language of medicine ---or for that matter, humans. "Hypertension" in medicine is about as descriptive as "rocky" is in astronomy. ("ICD-9 401.9: Unspecified essential hypertension" is about as descriptive as "a solid, rock-like mass")

@Afterthought "I see about 5 patients per week who do not know at least half of their family history. Genetic testing TODAY is cost effective for them; in the future, it will be ILLEGAL not to."

*Illegal* not to? This is both terrifying and terrifying. By this same logic, it's cost effective to get your blood pressure. Should it also be illegal not get a regular blood pressure?

The didn't perform a physical exam, they didn't do a HGBA1c, no PSA, looks like the didn't do a clinical assessment, just played with genome browsers and sequencers. How is that medicine? http://thegenesherpa.blogspot.com/2010/05/personal-genomes-in-clinical-…

The answer, it is not.

-Steve

@afterthought

You actually see patients and had a comment like that?
It is truly scary a clinician would suggest it illegal to refuse a test. What's next, Death Panels? Nice.......

-Steve

@ afterthought,
The possibility of using genetic testing to obtain a family history from a patient who can't is something to look forward to someday, but unless I am mistaken, here in the US we can't force anyone to be tested. As it is right now, most people would find the cost prohibitive, and good luck trying to get your HMO to pay for it.

23andMe gets scooped on hair curl genes

dgmacarthur — Wed, 11 Nov 2009 18:15:00 +0000

23andMe gets scooped on hair curl genes

Medland et al. (2009). Common Variants in the Trichohyalin Gene Are Associated with Straight Hair in Europeans. The American Journal of Human Genetics DOI: 10.1016/j.ajhg.2009.10.009

A couple of weeks ago I reported on a presentation by 23andMe's Nick Eriksson at the American Society of Human Genetics meeting in Honolulu, in which Eriksson presented data on a series of genome-wide association studies performed by the company using genetic and trait data from its customers.

Along with genetic analysis of a variety of other traits (such as asparagus anosmia and photic sneeze) Eriksson presented data on two novel regions significantly associated with hair curl, one close to the TCHH gene and a second near WNT10A (see the abstract for details). I noted at the time that 23andMe appears to be doing a pretty good job of running genome-wide association studies, although of course the real test of this is independent replication.

Well, now we have replication (of a sort) for at least two of 23andMe's novel findings - but unfortunately for the 23andMe crew the "replication" study has beaten them into print.

In this week's issue of American Journal of Human Genetics an Australian group report a genome-wide association study of hair curl that uncovered both of the novel regions picked out by 23andMe's scan (the very strong TCHH association is the headline finding, while WNT10A is mentioned briefly later in the text).

In a sense this is good news for 23andMe, in that it's good, independent evidence that the company's novel associations are robust. However, it's also bad news: not only has the company been scooped on the hair curl findings, but this is a clear illustration that there are few phenotypic niches sufficiently obscure for 23andMe to be able to work safely without worrying about competition from academic consortia.

The Australian group that produced the hair curl study (led by Nick Martin) has both the resources and the expertise to churn through the same sorts of commonly variable non-disease traits that 23andMe is well-powered to analyse, as their publication list illustrates. Other rivals have even greater capacity for scoopage: ailing biotech deCODE, for instance, has genetic and detailed trait data for a hefty chunk of the Icelandic population that can easily be used to unravel the genetic architecture of whatever common trait it decides to turn its attention to.

One major advantage that 23andMe possesses over any of its rivals is a highly actively involved participant base, many of whom will remain available and willing to answer online surveys and purchase additional genetic tests so long as the company can keep drip-feeding them interesting nuggets of genetic information about themselves.

Is that enough to maintain a profitable business? The two waves of lay-offs (one in June, and a more recent one in October) and the recent departure of co-founder Linda Avey from the company suggest that there may be some uncertainty about that even within 23andMe. Still, there's little question that the company has done more to establish the personal genomics industry than anyone else, and it's still far better-placed than either of its two major rivals, deCODEme and Navigenics. There are big changes coming in personal genomics, but I don't expect to see 23andMe toppled from its pedestal any time in the near future.

dgmacarthur Wed, 11/11/2009 - 13:15

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23andMe presents novel genetic associations at American Society of Human Genetics meeting

dgmacarthur — Sun, 25 Oct 2009 04:30:26 +0000

23andMe presents novel genetic associations at American Society of Human Genetics meeting

It's been an intensive week of genomics here at the American Society of Human Genetics meeting, and I haven't been able to grab time to blog as much as I'd have liked. In fact there's a whole load of genomics news I'll be trying to cover in some detail over the next couple of weeks; for the moment, though, I couldn't let today's presentation from personal genomics company 23andMe go by without at least some comment. (For other coverage of the conference, do check out Luke Jostins' blog coverage and the stream of live analysis on Twitter.)

The 23andMe presenter (Nick Eriksson) delivered an overview of the potential of the 23andMe cohort for association studies: all 23andMe customers have genetic information for over 500,000 common genetic variants, and they are also encouraged to provide self-reported phenotype data on a wide range of traits ranging from the presence of detached earlobes to longitudinal tracking of Parkinson's disease symptoms. Eriksson reported that the company now had sufficient numbers of returned surveys to perform genome-wide association studies for 22 traits, with sample sizes ranging between 2500 and 6000 individuals - reasonable sample sizes for an initial look at the genetic architecture of a complex trait.

The company seems to be doing a reasonable job of identifying and controlling for the various potential confounders that plague genome-wide association studies, such as population structure. However, 23andMe faces an unusual challenge that standard academic GWAS consortia don't: the possibility that a subject will give a biased trait report after seeing their own genetic data.

This was powerfully illustrated by results from the "athlete gene" ACTN3 (a gene close to my own heart). There was no association between the athletic performance-associated variant in this gene and self-reported sprinter/endurance preference in individuals who hadn't seen their genetic data - but in individuals who had already seen their genotype there was a marked shift towards carriers of the "sprint" or "endurance" allele self-identifying with those respective categories. In other words, people were altering their self-reported athletic affiliation on the basis of their genotype; Eriksson estimated that around 25% of individuals must be shifting their self-identification to explain the effect, a staggeringly large number.

Eriksson played down the potential impact of this effect, but this is still a rather worrying finding for a company relying on self-reported (and often quite subjective) phenotype data from a customer base that has often peeked at their genetic data before ever filling in a survey; at the very least there is potential for inflation of apparent association with known markers already in the 23andMe database. One way around this might be to provide some kind of incentive for customers to complete phenotype surveys before they ever see their genotype data, perhaps by providing discounts on future product updates.

Aside from this niggling concern, the major message from the talk is that 23andMe's approach works in terms of generating genome-wide significant associations for complex traits: the company has successfully replicated a series of known associations with eye, skin and hair colour, for instance. More interestingly, 23andMe has also nailed down a handful of genuinely novel genetic associations: a massively significant association between an olfactory receptor region and "asparagus anosmia" (the inability to smell asparagus in one's own urine), and two regions associated with hair curl.

These traits seem pretty trivial, but this is precisely the sort of area where 23andMe will be able to out-compete academic consortia, and these types of associations are also extremely (perhaps perversely) attractive to personal genomics customers; it's just cool to be able to see the region of the genome that underlies a trait you can see in yourself, and to follow the inheritance of these traits through a family. These types of associations won't contribute to clinical genetics, but they are likely to non-trivially boost 23andMe's appeal to consumers.

Will 23andMe be able to uncover novel associations with a greater relevance to disease genetics? I suspect their impact here will be much more modest, at least in the near future; academic consortia are generally vastly more well-powered to pick up disease risk associations given their more stringent quality control and phenotype definitions. However, it's important not to underestimate the importance of 23andMe's ability to recruit and maintain an active base of participants, and their Facebook-like viral marketing appeal (in which customers have an incentive to recruit other people). This may make it possible for 23andMe to tap long-term phenotypic change, such as the progression of symptoms in patients suffering from diseases such as Parkinson's.

It's been interesting to watch the perception of the genomics community towards 23andMe shift over time. There's still some hostility out there - and indeed, the first question directed towards Erikson was a needlessly combative and rather incoherent question about the ascertainment bias in 23andMe's sample towards wealthier individuals - but the strangeness of the 23andMe model is starting to wear off, and presentations like this one will no doubt help to convince scientists that this is a company that at least is capable of doing solid science.

There's one other small nugget of data worth mentioning. It's always been hard to get a solid estimate of the number of customers in 23andMe's database, but we now have a conservative lower bound: the company has at least 6,000 unrelated individuals of European ancestry enrolled who have taken phenotype surveys, suggesting a total active (i.e. engaged in phenotype surveys) customer base substantially higher than this. I don't think this number would surprise many regular readers, but it's a useful antidote to the sorts of ridiculously low recruitment numbers I've heard quoted by personal genomics critics.

dgmacarthur Sun, 10/25/2009 - 00:30

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23andMe

ashg2009

consumer-driven research

direct-to-consumer genetic testing

participant-driven research

personal genomics

Chinese summer camp to offer genetic tests for IQ, athletic performance, emotional control

dgmacarthur — Thu, 06 Aug 2009 10:00:00 +0000

Chinese summer camp to offer genetic tests for IQ, athletic performance, emotional control

CNN reports:

At the Chongqing Children's Palace, experts are hoping to revolutionize child-rearing with the help of science. About 30 children aged 3 to 12 years old and their parents are participating in a new program that uses DNA testing to identify genetic gifts and predict the future.

The test is conducted by the Shanghai Biochip Corporation. Scientists claim a simple saliva swab collects as many as 10,000 cells that enable them to isolate eleven different genes. By taking a closer look at the genetic codes, they say they can extract information about a child's IQ, emotional control, focus, memory, athletic ability and more.

"For basketball, we can test for height and other factors," said Dr. Huang Xinhua, a leading scientist on the project. "We also test listening ability so that can tell us if (the child) might be talented at music." [my emphasis]

A quick note for any Chinese parents considering having this test performed on their children: you're wasting your money (and we're not talking small change - the test costs US$880).

The genetic variants that are currently known to affect traits such as athletic performance and height explain only a tiny fraction of the variation in these traits, so predictions made from genetic tests are extremely weak. In fact, for a trait such as height, parents can make substantially better predictions simply by measuring their own height than they can using the best that modern genetics has to offer.

Eleven genes could only ever capture a tiny fraction of the variants affecting these traits; and it's also worth noting that the vast majority of genetic research into complex traits has been done in Europeans, making predictions in East Asians (where the genetic architecture is likely to differ non-trivially) very problematic.

The company's claims are frankly absurd:

Dr. Huang said the testing can even help project careers down the road.

Examining one child's results, he told CNN: "This child is very thoughtful and focused, so I suggest she go into management."

There are no convincing, predictive associations between genetic variants and "thoughtfulness" - this is a scam, pure and simple, preying on parents' willingness to believe in the power of science and to pay through the nose for anything they think might give their child an extra edge.

Unlike a lot of commentators on this story, I've got nothing fundamentally against the idea of using genetics to make predictions about a child's future, and on guiding the activities a child engages in based on those predictions. Here's the thing, though: this only makes sense if the predictions are both accurate and relevant, and right now the predictions from genetics regarding complex traits are neither. Parents should save their money for more useful ways to enrich their children's lives.

It will be very interesting to see how the differing cultural mores in China and other East Asian countries shape the adoption of direct-to-consumer genetic testing in the region; I think most of us expect that these countries will be far less squeamish than the West about taking full advantage of genetic information. That makes East Asia an extremely attractive target for all manner of DTC genetic testing companies.

As an example, I was recently pointed to this Chinese copy of personal genomics company 23andMe. Here are two screenshots comparing the Chinese version with the actual 23andMe site:

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dgmacarthur Thu, 08/06/2009 - 06:00

Tags

genetics of intelligence

genetics of personality

personal genomics

Whether it's a scam or wishful thinking, at least you don't see political correctness that plagues this country.
Whether you like it or now, future genetics may well be what is described in Gattaca, once more genes, SNP's and their confounding effects are better understood in the future.

If a world with gene therapy like Gattaca means a 50% increase in the average per capita contribution to GDP, I'm all for it.

I'm going to brush up on my Mandarin.

IQ is not only related factor for emotional control

http://www.mygene23.com seems to attract a lot of eyeballs. Personal Genetic Service is a huge market, which nobody will deny.

Genetics of complex traits in Europeans and East Asians: similarities and differences

dgmacarthur — Tue, 28 Apr 2009 09:00:00 +0000

Genetics of complex traits in Europeans and East Asians: similarities and differences

Cho, Y., Go, M., Kim, Y., Heo, J., Oh, J., Ban, H., Yoon, D., Lee, M., Kim, D., Park, M., Cha, S., Kim, J., Han, B., Min, H., Ahn, Y., Park, M., Han, H., Jang, H., Cho, E., Lee, J., Cho, N., Shin, C., Park, T., Park, J., Lee, J., Cardon, L., Clarke, G., McCarthy, M., Lee, J., Lee, J., Oh, B., & Kim, H. (2009). A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits Nature Genetics, 41 (5), 527-534 DOI: 10.1038/ng.357

A paper just released in Nature Genetics takes the most comprehensive look yet at the genetic factors underlying complex traits in an East Asian population, using a large sample of Korean individuals.

The researchers used a genome-wide association study to look at eight medically relevant traits: body mass index (BMI), waist-to-hip ratio, height, systolic and diastolic blood pressure, pulse rate, and measures of bone density in the arm and leg. The results reveal both similarities and intriguing differences in the genes contributing to trait variation in East Asian and European populations. For instance, while many of the genomic regions associated with BMI and height were the same in this study as those previously identified in European cohorts, there were a number of replicated variants associated with the other traits that have not previously been found in large European studies.

Why the differences? In some cases the answer is obvious: the genetic
variant differs in frequency between Europeans and Koreans, altering
the power of genome-wide studies to detect the association. In other
cases the variant is at a similar frequency in the two
populations, suggesting that the effects of certain genetic variations
may depend on variants elsewhere in the genome (i.e. a so-called
"genetic background" effect).

During the kerfuffle over the value of genome-wide association studies (GWAS) a couple of weeks ago much was made of the fact that even if genetic variants are not strongly predictive, they can still provide insight into the underlying biology of a common disease. The problem with this approach is that genes that play a major role in the disease process will not be picked up by GWAS if they don't happen to contain a common variant that alters their function in that population.

By surveying multiple human populations by GWAS, however, we increase the pool of common genetic variants - and therefore increase the odds that any given disease pathway gene will be picked up in at least one GWAS. In addition, because different populations show different patterns of association between neighbouring genetic variants (linkage disequilibrium), looking in multiple populations can be extremely useful for dissecting out which variants are actually causative and which are mere bystanders.

With those goals in mind, you can expect to see many more GWAS of non-European populations over the next couple of years, and some explicit comparisons of the differing genetic architecture of complex traits between populations. Exciting times for those of us interested in the genetic and evolutionary basis of between-population differences...

dgmacarthur Tue, 04/28/2009 - 05:00

Tags

predictions

race

NIH offers $2 million to fund mapping of genetic variation to gene expression

dgmacarthur — Thu, 02 Apr 2009 16:30:00 +0000

NIH offers $2 million to fund mapping of genetic variation to gene expression

GenomeWeb Daily News points to a new funding opportunity from the US National Institutes of Health (NIH) for researchers interested in studying the link between genetic variants and variation in the expression levels of genes.

This is an incredibly important area of research. Genome-wide association studies have recently uncovered vast numbers of DNA regions linked to common diseases (the latest estimate I've heard suggests around 400 common genetic variants associated with 75 different diseases or traits) - but we still don't have a clue how the majority of these regions actually alter disease risk.

However, it's becoming increasingly clear that very few of these association signals are due to changes in the sequence of the proteins produced by genes. Instead, it seems likely that many of the underlying genetic variants affect human health through changes in gene expression - basically, by alterations in the levels of messenger RNA produced by a gene, with downstream effects on the amount of the protein produced by that gene. Proteins, by and large, are the molecules that actually do stuff (like holding cells together, or driving the chemical reactions required for life), so such changes can have profound effects on human health.

The link between genetic variation and gene expression has thus been a target of intensive research over the last few years, a fair chunk of which has been performed by colleagues at the Sanger Institute. The major limitation of this research is that it has almost exclusively been performed using a single type of cell - immortalised lymphoblasts, blood-derived cells with the handy property of being able to grow and divide in a Petri dish essentially forever.

Although this research has already answered fundamental questions about the link between genetic variants and gene expression, it provides insight into just one of the hundreds of cell types dwelling within the human body. Obtaining a broader picture of the way that genetic variation alters disease risk will require performing this analysis in many different tissues in hundreds of humans, all of whom have very detailed information on patterns of genetic variation.

That's the aim of the NIH's Genotype-Tissue Expression (GTEx) project, the focus of the current funding boost. GTEx is a pilot project that will look at the correlation between genetic variation and gene expression in many different tissues, collected during autopsy or organ transplant procedures from 160 donors. In other words, in addition to lymphoblasts, researchers will have access to data from tissues like liver, heart and brain that are typically off-limits - and that in turn will provide insight into diseases that primarily affect these tissues, information that simply couldn't be gleaned from studies of cultured lymphoblasts.

The NIH funding is aimed at supporting the development of new methods for detecting links between DNA-level variation and gene expression. This is extremely timely: new sequencing technologies offer images of astonishing resolution of patterns of gene expression, but techniques for making full use of these data are still in their infancy. A targeted cash infusion is a very handy incentive to drive these techniques forward.

genetics of gene expression

dgmacarthur Thu, 04/02/2009 - 12:30

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Instead, it seems likely that many of the underlying genetic variants affect human health through changes in gene expression

Changes or differences? If it's changes, then using tissue after the disease has progressed doesn't seem sensible to me: you don't know what else has happened in between.

I'll also pimp a short commentary of mine where I pointed out that gene expression studies are useless at telling us what's really going on, because they say little about the underlying physiology.

Hi Bob,

I guess I meant "differences", i.e. people with different genotypes have different levels of gene expression.

I agree with your point about the dangers using tissue late in disease progression - by this stage there's every chance that the primary gene expression differences have been obscured by secondary changes (e.g. fibrosis, inflammation, etc.). However, most of the studies here aren't actually looking at disease patients: they're looking at genetic control of gene expression across a large cohort of healthy (or at least unselected) individuals. This doesn't necessarily provide deep insight into highly disease-specific processes, but it does allow a dissection of the effects of common disease-associated variants on expression, as well as some intriguing insights into the generalities (here's two examples).

Thanks for the link to your paper - I especially enjoyed the carefully understated first paragraph! I agree with your argument regarding the likely irrelevance of most gene expression changes to disease; given the sheer number of common eQTLs that have been discovered recently, I think it's likely that you're correct that the majority of these have essentially no effect on overall phenotype.

However, that's not to say that all of them are neutral, and I'd still argue that it's likely that a significant proportion of disease risk variants (possibly the majority) are the result of either direct or indirect effects on gene expression.

Genes vs environment: a false dichotomy

dgmacarthur — Wed, 25 Mar 2009 07:45:55 +0000

Genes vs environment: a false dichotomy

Neuroscientists Sam Wang and Sandra Aamodt have a guest post on Olivia Judson's NY Times blog discussing the complex interplay between genes and environment in the determination of personality traits. A taste:

So some of the effects that we call "genetic" (or "nature") are the
indirect result of people being drawn to particular environments
because of their personality. Or to put it another way, some
"environmental" (or "nurture") effects are actually attributable to
genetic tendencies.

It's worth noting that similar effects can occur for other traits: for instance, a genetic variant that increased sugar cravings or decreased motivation to exercise could have an effect on obesity risk; a variant that increased susceptibility to a specific virus might increase the risk of auto-immune diseases triggered by viral infection. In each case, the genetic variant increases disease risk indirectly by altering exposure to an environmental risk factor.

gene-environment interactions

dgmacarthur Wed, 03/25/2009 - 03:45

Tags

genetics of personality

gene-environment correlation
gene-environment interaction

good ideas....

you gotta be kidding me... doesn't anyone read Fisher anymore??
ok.. even g.c.williams/
or, if you're a behaviorist, at least go back to jerry.hirsch.

nah. lets stick with Fisher.
P=G+E
after one breaks down (G) into additive (A), dominance (D) and epistasis (I) ... G*E and r(GE), are, mostly, minor components....

btw -- twin studies inheritantly overstimate all of these components (even with some of the newer statistical models), but are superb for elucidating environmental influences...
:)

Race and intelligence: the debate continues

dgmacarthur — Thu, 12 Mar 2009 08:45:26 +0000

Race and intelligence: the debate continues

I posted a while back on two duelling essays in Nature on the intensely controversial subject of whether scientists should be permitted to study group differences in cognition. Nature now has a series of correspondence on the topic in its latest issue.

Firstly, there are rebuttals from the authors of the two original essays: Steven Rose argues that the debate is dead and that reviving it serves no purpose, while Ceci and Williams argue (substantially more convincingly, in my opinion) that Rose's declaration of these areas of research as invalid is premature.

Some of the other opinions are predictable: two letters, for instance, simply dismiss the use of IQ as a measure of intelligence. A third letter in a similar vein is more subtle and interesting: Kathryn Holt argues that IQ is an overly simplistic measure, but that more detailed analyses of cognitive differences may prove illuminating:

So, given that we have logical reason to hypothesize about differences
in cognitive abilities, why would we expect to measure these by using a
single number such as IQ, which suggests there must be a hierarchy of
cognitive function? The prediction surely is that each population will
adapt to be better at the particular cognitive tasks that are most
important for survival in its own environment. If this is the case,
then identifying these (potentially adaptive) differences in cognitive
ability, and searching for associations with genetic variants, could
provide fascinating insights into how our brains work.

This makes good sense; if human populations have indeed undergone some level of genetic adaptation to meet differing cognitive demands (which seems entirely possible given what we know about recent human evolution), then investigating group differences may provide useful insights into the molecular architecture of cognition.

One of the most well-respected researchers in the field of group differences in cognition, Jim Flynn, weighs in with a careful and measured response:

As the philosopher John Stuart Mill points out, when
you assert that a topic is not to be debated, you are foreclosing not
some narrow statement of opinion on that topic, but the whole
spiralling universe of discourse that it may inspire. Mill thought that
only someone so self-deluded as to think his own judgement was
infallible could wish to circumscribe an unpredictable future in this
way.

Rose should be very certain he is correct. If
not, and if he converts the rest of us, only Jensen and those of his
persuasion [i.e. advocates of group differences] will publish; and they will win the minds of students
because the rest of us have all adopted a policy of unilateral
disarmament.

Finally, Gerhard Meisenberg appears to advocate the widespread use of genetic engineering (or selective breeding?) should any genetic basis for group differences in cognition be uncovered:

By not investigating the race-intelligence link, we not only perpetuate
ignorance and the prejudice that thrives on ignorance. We also deprive
ourselves of the possibility to tackle the existing inequalities, first
by a judicious development policy and -- should genetic differences
indeed be important -- by eventually changing the allele frequencies of
the offending genes. We should not get stuck in the twentieth-century
assumption that environments are changeable but genes are not. This
will no longer be the case in the twenty-first century. [my emphasis]

This is not a debate that will be resolved any time soon, but it is a credit to Nature that they have permitted such a robust exchange of views on this rather dangerous topic within their pages.

dgmacarthur Thu, 03/12/2009 - 04:45

Tags

genetics of intelligence

race

A short essay on this topic:

FASTER EVOLUTION MEANS MORE ETHNIC DIFFERENCES
by Jonathan Haidt
http://www.edge.org/q2009/q09_4.html#haidt

Bob and Razib,

Let's start that again, shall we?

Bob - Razib is trolling; don't take the bait.

But ... but ... I enjoy getting outraged. It's the most fun I've had all day.

OK, let's be serious. I agree with your conclusion. One thing that interests me is the technical aspect of estimating genetic variation across populations (it's one of the things I work on). It's difficult in any system (see this commentary for a discussion of some of the issues). For humans, I think we would need cross-fostering across populations and good pedigree information (or a lot of cross-fostered twins). Such data would be fascinating to play with (whatever the trait), but I'm not holding my breath waiting for it to be collected.

For humans, I think we would need cross-fostering across populations and good pedigree information (or a lot of cross-fostered twins). Such data would be fascinating to play with (whatever the trait), but I'm not holding my breath waiting for it to be collected.

international adoption. there is suggestive data out there.

i hope you did get to see my last comment....

Me as pretty much uneducated guy interested in science doesn't get what's wrong here. What is science about again? Should we ban research because it could reveal some inconvenient truth about reality, like that Swazi people may actually be better at math than Vietnamese and native Americans less aggresive towards strangers than Mongolian? It may turn out that some people with black skin are actually much smarter than most people with white skin, given the same environmental conditions and education. So?

I'm vegetarian, I'm anyways following non-anthropocentric moral values. It won't change much for me if science discovers that I as German have a lower general intelligence (whatever that is) than Polish people or vice versa.

Indeed, some racists may use any findings to back their ideas. But it may also lead to the implementation of a broader circle of ethics, adequate for a future that may hold more diverse intelligence than we see today.

If race didn't exist, would we have to invent it?

I think Rose is simply retreating in some disarray from a previous trenchant position against sociobiology in general to (in his eyes only) a more defensible position against intelligence genetics (why does that have to be confined to race?). Its not ethics its right on lefty politics 80s style.

That said whilst I have no ethical objection to tackling this problem I greatly doubt we presently have the methodology or tools to do so. Once we start to really get to grips with the genetic associations of variants with simple phenotypes or common diseases-- then we can start to worry about associations with nebulous traits that we cannot yet define.

Predicting eye colour from genes

dgmacarthur — Tue, 10 Mar 2009 12:15:35 +0000

Predicting eye colour from genes

Fan Liu, Kate van Duijn, Johannes R. Vingerling, Albert Hofman, AndrÃ© G. Uitterlinden, A. Cecile J.W. Janssens, Manfred Kayser (2009). Eye color and the prediction of complex phenotypes from genotypes Current Biology, 19 (5) DOI: 10.1016/j.cub.2009.01.027

In a recent post I noted that genetic tests to predict adult height are still a long way off being accurate; currently, known genetic variants can predict just over 5% of the variance in height, as opposed to 40% predicted using a simple algorithm based on the heights of both parents. The genetic complexity of height means that trying to screen embryos for this trait using pre-implantation genetic diagnosis is likely to be little more than an exercise in frustration.

However, that's not true for all traits. In several recent posts I've mentioned eye colour as one relatively genetically simple trait that would prove amenable to embryo screening, and indeed there has already been at least one US fertility clinic offering such screening to couples undergoing IVF (although that offer has now been withdrawn).

A paper in the most recent issue of Current Biology puts some numbers on the predictive value of genetic testing for the prediction of eye colour. The authors examined all of the 37 variants (in 8 separate genes) previously reported to have an association with eye colour in a sample of 6,168 Dutch of European ancestry, and assessed the predictive value of these markers alone and in combination.

The results were clear: with just six genetic markers, individuals with blue or brown eye colour could be predicted with over 90% accuracy*; the accuracy for predicting intermediate colours (e.g. green) was somewhat lower at around 72%.

Adding further markers had rapidly diminishing returns, with the last 15 markers adding essentially nothing further in terms of predictive value (these markers were typically captured by other variants within the same gene).

The authors note that "[t]he genetic prediction values obtained here for blue and brown eyes in
Europeans represent the highest accuracies revealed so far in genetic
prediction of human complex phenotypes." This makes for a pleasant change from the results for most disease-related traits, where common genetic variants have generally provided frustratingly little predictive power for risk prediction.

In addition to being a tempting target for "cosmetic" genetic screening by parents undergoing IVF, eye colour genes will no doubt prove useful in forensic applications - being able to predict any physical traits from trace DNA left at the scene of a crime will at least occasionally be useful for investigators. However, the researchers note that their results should only be regarded as applying to individuals of European ancestry; different populations are known to have different genetic determinants of pigmentation.

* Strictly speaking, the researchers showed that the area under the ROC curve was greater than 0.9 for blue and brown eyes and 0.72 for green eyes; this can be interpreted as the probability that a randomly chosen positive instance would be ranked higher than a randomly chosen negative one.

dgmacarthur Tue, 03/10/2009 - 08:15

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pre-natal genetic diagnosis

I believe that the technology will never reach 100%. There will always exist a small chance that such predictors and markers just happen to fall into the statistically extreme area, so we can never guarantee a prediction of eye color. However, eye color doesn't matter much anyways, so let parents predict all they want. It has no tangency with intelligence or physical superiority.

Predicting height: the Victorian approach beats modern genomics

dgmacarthur — Tue, 03 Mar 2009 06:30:00 +0000

Predicting height: the Victorian approach beats modern genomics

Yurii S Aulchenko, Maksim V Struchalin, Nadezhda M Belonogova, Tatiana I Axenovich, Michael N Weedon, Albert Hofman, Andre G Uitterlinden, Manfred Kayser, Ben A Oostra, Cornelia M van Duijn, A Cecile J W Janssens, Pavel M Borodin (2009). Predicting human height by Victorian and genomic methods European Journal of Human Genetics DOI: 10.1038/ejhg.2009.5

Human height is a strongly genetic trait: in well-nourished Westerners somewhere in the vicinity of 80-90% of the variation in height is due to genetic factors; if your parents are tall, there's a very good chance you will be too. That means that if we understood the genetic factors that influenced height we could predict the future height of a child (or even an embryo) with a reasonable degree of accuracy.

However, developing that genetic understanding has proved extremely difficult. It turns out that height is also the classic model of a genetically complex trait: a spate of very large recent genome-wide association studies has nailed down over 50 different regions of the genome that affect height, which in total explain less than five percent of the overall variation - suggesting that hundreds (if not thousands) of individual genetic variants contribute, most of them nudging us upwards or downwards by just a few millimetres.

Height is not the only human trait to demonstrate such a convoluted molecular basis; aside from a few unusual traits such as skin pigmentation, the majority of traits that vary between humans are genetically complex. This is one of the reasons why embryo screening for traits like height or IQ is unlikely to be effective in the near future.

A recent paper in the European Journal of Human Genetics (also covered by Dienekes) illustrates this point by comparing the predictive power of modern genetics with a method for height prediction developed back in 1886 by Sir Francis Galton. The results are a humbling reminder of just how much we have to learn about the genetic architecture of variable human traits.

The study looked at all 54 of the markers identified by the three studies linked above as being associated with height, and used these markers to generate a "genotypic score" - basically a count of the number of "tall" variants that each individual carried. This score was generated for 5,748 individuals of known height.

This graph shows the results: sex- and age-adjusted height are shown on the vertical axis, and genotype score on the horizontal axis.

The blue line shows the slope of best fit for the data; you can see that the individuals forms a diffuse cloud around the line, with a barely discernible upwards trend. In fact, genotype score explained just 3.8% of the variance in height, although the authors could squeeze this up to 5.6% by carefully weighting the markers. (For the curious, the red lines represent the mean residual height in people coming from top and bottom 5% of the profile distribution.)

That's a fairly disappointing result from the best set of markers that modern genomics has to offer. Adding insult to injury, the authors go on to compare this result to the predictive power of the 123-year-old Galtonian height prediction method, which relies simply on the average deviation of the two parents from the population average (corrected for age and sex). This measure was calculated for a smaller set of 550 individuals for whom parental height data was available.

Here's the data for this approach:

In this graph, the blue line is the best fit, and the green line has a slope of 1; the difference between these two lines is due to regression toward the mean. The correlation between this predictor and measured height is much stronger than for the genotype score above: this measure predicts around 40% of the variance in height, 6 to 10 times more than is explained by genotype score.

The two measures were highly correlated, as you would expect, meaning that adding genetic data to the Galtonian method only improved the variance explained by ~1.3%.

The difference in predictive power between these two methods (which are, in effect, measuring the same thing) is a powerful testament to our current ignorance of the genetic determinants of human traits.

Of course, that ignorance is a temporary state. I know there is at least one massive meta-analysis of height genome-wide association data that should be published early this year, and will add a few more dozen common markers; the hunt for rare height-altering variants will take a little longer but should bear fruit over the next couple of years.

So, will adding more and more genetic markers eventually provide a useful predictive test that exceeds the power of simply measuring parental heights? Well, here's what that first graph would look like under the hypothetical scenario that we knew everything about height genetics (i.e. had markers capturing the full 80% of the heritable variance):

You can see immediately that the predictions made under this hypothetical future scenario would be extremely accurate. However, whether we can actually find all of the genetic variants underlying height - or even the majority of them - remains to be seen. It's entirely possible that a large fraction of this variation is determined (for instance) by very large numbers of variants with extraordinarily small effect sizes, or by subtle non-additive interactions, in which case the sample size required to characterise the full spectrum of variants may be larger than the population available for sampling. Now that would be a disappointing outcome.

It's worth noting that the better performance of the Galtonian approach is not universal. For some traits with low heritability (such as some serum lipid levels) the Galtonian approach performs even more poorly than current genetic markers; this indicates that it won't be much longer before genetic tests are better than family history for risk prediction, at least for a subset of traits.

Still, this paper is a timely reminder of the primitive state of our current understanding of complex trait genetics, and just how far we have still to go before personal genomics can provide useful, novel predictions for the majority of human traits.

dgmacarthur Tue, 03/03/2009 - 01:30

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