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Exclusive interview with genomic researcher Davide Piffer

19 Sunday Jan 2020

Posted by pumpkinperson in Uncategorized

≈ 102 Comments

Tags

ancient DNA, cold winters, Davide Piffer, ethnicity, IQ, John Hawks, Michael Woodley, mutations, Neanderthals, polygenic scores, race, Richard Lynn

I am extremely honored that Davide Piffer (who has a blog) was kind enough to give our community an exclusive interview. While the leading geneticists in academia have explained only about 10% of the variance in IQ (or its proxy education) at the individual level, Piffer working on his own has reported near perfect correlations between the mean IQs of entire ethnic groups and their polygenic scores, making him a rock star in the HBD community. Virtually no one else on the planet is doing this kind of cutting edge research (at least not publicly).

In retrospect it makes perfect sense that aggregated data should correlate much better than individual level data. Imagine you visited every country in Eurasia and asked only the first person you met in each country their height. Such a small sample size (n = 1) from each country would tell you nothing about which individual country was taller than which, but if you averaged all the heights from the European countries and compared them to the average heights from the Asian countries, you’d learn a lot about which continent was taller. That’s because the small sample size at the level of individual countries is multiplied by the large sample of countries in each continent.

It’s the same with genomically predicting IQ. The small sample of single nucleotide polymorphisms (SNPs) sampled in each individual is multiplied by the large number of individuals sampled in each ethnic group, so while individual predictions are weak, group predictions are strong because individual error cancels out in the aggregate.

Below is my exclusive interview with Piffer. The interview has been lightly edited to remove typos and other mistakes. I began by asking him about table 5 in a 2019 paper he wrote. My statements are in red, while Davide’s are in blue.

Table 5 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

PP: I’m very impressed by your work. But the correlation between PG score & mean IQ is so high in table 5 of Piffer (2019) that it seems too perfect. What would you say to skeptics who think you cherry-picked SNPs or manipulated your formulas to get such perfect results?

DP: Thanks. I didn’t cherry pick SNPs. I used the polygenic score provided by Lee et al and you can see that different PGS construction methods lead to same results… I used EA, EA Mtag, etc, weighted and unweighted..they all give same results. Also my paper replicates my previous findings and what I had predicted from theory years ago. The IQs aren’t cherry picked either because I used the same as I used in previous papers to avoid post hoc results.

PP: In table 1 of Piffer (2019), Peruvians & Colombians seem to have higher polygenic scores than the black populations, yet in Figure 11, Africa scores higher than the Americas. So who has higher polygenic scores: sub-Saharan Africans or Amerindians?

top part of table 1 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data
rest of table 1 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data
Figure 11 from the paper Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data

DP: Peruvian and Colombian aren’t pure. They are substantially mixed with Europeans. The groups in figure 11 are natives, so they better reflect the unadmixed population. Also the latter are from low coverage genomes with fewer markers so less reliable. I am working on a high coverage version of same datasets but it will take a while due to my limited funds.

Do you have some basic experience in bioinformatics? I am just looking for someone who could run the code on their laptop because it’s taking me a week to impute each chromosome. So I need to run it on multiple computers. But hey no bother…I will do it myself, it will just take it longer.

PP: No sadly I do not have experience with bioinformatics. But I can ask my blog & twitter readers if anyone has such experience and is willing to volunteer their time.

On table 5 of Piffer (2019) the African American PGS (GWAS sig) is 1.836 lower than the NW European PGS. But since African Americans are only 76% non-white (Bryc et al. 2015), can we roughly infer that un-mixed blacks would be 1.836/0.76 = 2.416 below NW Europeans, giving them a PGS score of 46.834?

DP: yes…also you have unmixed native Africans in the other tables. Kenyans, Yoruba, Mende Sierra Leone, etc

PP: In table 5 Latinos have a PGS (GWAS sig.) of 48.654. Do you think this could be used to estimate the PGS of unmixed Amerindians because according to Bryc et al, 2015, Latino Americans are 65.1% white (mostly southern European), 6.2% black, 18% Amerindian, and 11% unassigned, though the unassigned is broader East Asian/Amerindian so should probably be counted as Amerindian. Since you report the PGS for Southern Europeans and since I estimate the the PGS for pure blacks at 46.834, using simple algebra, I estimate unmixed Amerindians would have a PGS of 47.510.

DP: yes, but you should also cross-check these with the other table with scores for Peruvians and Mexicans and see if they converge.

PP: Good point. In one of your data sets you find a 0.57 correlation between PGS and latitude. Do you agree with Lynn’s cold winter theory of how racial differences in intelligence evolved?

DP: in part, yes. but it doesn’t explain the low Amerindian IQ because Native Americans were in Siberia during the Last Glacial Maximum and then they moved to North America at the end of it, which is also a cold region…So I think most of the differences are due to farming and civilization

PP: Well Lynn argues the anomalies can all be explained by population size. Low population races like Arctic people, Amerindians, Australoids, Bushmen, & pygmies have lower IQs than their climates predict because there weren’t enough positive mutations. Meanwhile high population races like East Asians, whites, South Asians, and West Africans have higher IQs than their climates predict. This would also explain why Neanderthals had lower IQs than their climates predict.

DP: but these SNPs are common among the races..the differences are explained by these common SNPs, not pop specific mutations. pop size is probably related to it through higher competition for resources selecting for higher IQ.

PP: I see…so then it was probably farming and civilization as you say. Just as cold climate boosted IQ because it was a novel environment to adapt to, so was farming, civilization and the literacy and numeracy requirements it imposed. Of course Amerindians also independently created civilization but most remained hunter-gatherers.

DP: yes… plus we don’t know how many of these SNPs are just life history or personality traits like C. stuff that farming selected for. most of them are related to g but a subset will also be related to conscientiousness. Emil et al in their Psych paper vetted their association with g in a sample though so I guess they must be genuine associations with IQ for the most part.

PP: Yes, because no one has given a huge sample (n = 1 million) of genotyped people a highly g loaded test. A perfect study would get a sample of 1 million people (from all over the world) and give them an extremely culture reduced test with many subtests to maximize g loading (i.e. block design, draw a person in the sand, name as many body parts as you can in 1 minute in your own language, pictorial oddities etc) and then enter the composite score, DNA and human development index of each person into a computer and have machine learning create a multiple regression equation predicting IQ using HDI & genomic variants as independent variables. By using such a diverse and global sample, one finds the genomic variants that correlate with IQ everywhere and thus are most likely to be causal.

DP: yes.

PP: Now that the neanderthal genome has been published, why haven’t you tried to estimate their polygenic score? Richard Klein argues that before about 50 kya, modern humans and neanderthals had similar intellect, but suddenly around 50 kya there was a genetic brain change that allowed modern humans to leave Africa, colonize every continent, replace neanderthals & invent art & complex technology. Testing this hypothesis was the main motivation to sequence the neanderthal genome so there’s enormous interest in their intelligence, even in mainstream science.

DP: yes that’s the next step…we’re analyzing genomes from Bronze age now, but Neanderthal would be good. But funds are limited for this kind of research and I am not working in academia.

PP: Above you rejected Lynn’s population size mutation theory on the grounds that all races have all the known IQ related genomic variants, however it also seems you have no high coverage genomes from low population isolated groups like pygmies, bushmen, australoids, arctic people & pure Amerindians. Is it plausible that high coverage genomes of these groups would show they are missing some of the IQ enhancing mutations that appeared in the last 15,000 years?

DP: What I am saying is that you can see a difference even at the common SNPs in their frequencies. I cannot rule out that they are also missing these mutations but that would be an additional factor.

PP: Do you agree with John Hawks’s theory that positive selection in the last 5000 years has been a hundred times faster than in any other period of human evolution because of the explosion of new mutations & environmental change? This is the exact opposite of Gould who argued we have the same bodies and brains we’ve had 40,000 years ago and all subsequent change has been cultural not biological.

DP: from a purely theoretical point of view, yes, but one would need to study ancient genomes to empirically vet that hypothesis.

PP: Is there any strong evidence in support of Michael Woodley’s theory that white genomic IQ has declined by 10 or 15 IQ points since the Victorian era?

DP: I computed the decline based on the paper by Abdellaoui on British [Education Attainment] PGS and social stratification and it’s about 0.3 points per decade, so about 3 points over a century.

It’s not necessarily the case that IQ PGS declined more than the EA PGS..if anything, the latter was declining more because dysgenics on IQ is mainly via education so I think 3 points per century is a solid estimate

Thank you Davide Piffer for this interview. As mentioned above, you can find more of Davide’s thoughts on his blog.

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A near perfect correlation between ethnic IQ & ethnic DNA

17 Friday Jan 2020

Posted by pumpkinperson in Uncategorized

≈ 40 Comments

Tags

Davide Piffer, ethnicity, IQ, polygenic scores, race

Davide Piffer looked at 2,404 genomic variants found to predict education (a rough proxy for IQ) and used these to create polygenic scores of eight ethnic groups reared in First World conditions. He then compared the polygenic scores with the mean IQ of each group and found a 0.979 correlation.

Table 5 from Evidence for Recent Polygenic Selection on
Educational Attainment and Intelligence Inferred
from Gwas Hits: A Replication of Previous Findings
Using Recent Data
by Davide Piffer, 2019

The line of best fit allows us to predict the mean IQ of any group from their PGS (GWAS sig.):

Mean IQ = 9.31(PGS (GWAS sig.)) – 358

Given the 0.979 correlation, genotype predicts IQ remarkably well: Finnish 102, Ashkenazi 108, Southern Europe 99, Estonia 100, NW European 100, African American 83, Latino 95, East Asians 105.

So while our genomic predictions of IQ remain poor at the individual level, Piffer is showing we can predict the mean IQs of ethnic groups with incredible precision, at least when they’re all reared in similar countries.

Because we have only found a tiny fraction of the genetic variants associated with IQ (or its proxy education), the margin of error for predicting any one person’s IQ remains high. But when you try to predict the average IQ of an entire ethnic group, the overestimates and underestimates cancel each other out, and there’s a near perfect correlation between the mean polygenic score and the mean IQ.

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Polygenic IQ scores

15 Tuesday Oct 2019

Posted by pumpkinperson in Uncategorized

≈ 132 Comments

Tags

95% confidence interval, Gregory Clark, IQ, Neanderthals, polygenic scores, Richard Klein, standard error, Upper Paleolithic Revolution

Commenter “Some Guy” had some questions about polygenic scores for me. His questions are in block quotes with my answers directly below each one.

How good do you think polygenic scores will have to get before they start getting used on an individual level? Like within how many SDs of the true IQ/g/educational achievement?

If one’s polygenic score is extreme enough, it doesn’t have to be very accurate at all to give useful information. For example, let’s say you have several embryos to choose from and one has a polygenic education score of +5 SD. Even though such scores only predict 12% of the variance, because +5 SD is so extreme, you can be about 97% confident that embryo will grow up to be more educated than the average person (assuming he or she is raised in a society similar to the one from which the stats were derived).

One problem with polygenic scores is they don’t seem translate well from one culture to another, suggesting they’re more correlative than causal.

The uses I can think of is to identify children with high potential from poor backgrounds, or as an environmentally unbiased entrance “exam” for schools etc.

What I would like to see them be used for is to estimate the IQs of historical Geniuses like Albert Einstein and to estimate the IQs of ancient human populations. For example Richard Klein believes there was a major genetic change in human cognition that occurred about 50 kya that allowed us to suddenly spread from Africa, replace the Neanderthals, colonize the globe and create representational art. If we compared the polygenic scores of humans both before and after the upper Paleolitic revolution, we could test this idea. Similarly Gregory Clark believes rapid genetic evolution in Europe allowed the industrial revolution.

I would also love to see polygenic IQ scores for the Neanderthals, assuming they would be meaningful in a group that culturally and genomically distinct.

What sort of PGS-IQ correlation would result in polygenic scores that are say within 1 SD of the true IQ? I know you often calculate standard errors from correlations, mind sharing the formula/method?

Within 1 SD with degree of certainty? If you mean with 95% certainty, you would need a correlation of 0.85+ which I doubt will ever be achieved. Even the correlation between two different IQ tests is seldom that high.

The method is to square the correlation to get the percentage of the variance explained, and then subtract that value from 1 to see what percentage is left unexplained.

So for example a PGS that correlated 0.85 with IQ explains 72% of the IQ variance, thus leaving 28% unexplained.

The variance is defined as the standard deviation squared, so since the IQ standard deviation is set at 15, the variance is 225, and 28% of 225 is 63.

The square root of 63 is 7.9 which is what the standard deviation would be if everyone had the same PGS. This is also known as the standard error of the estimate. Now in a bell curve, 95% fall within 1.96 of the mean, so multiplying 7.9 by 1.96 tells us that 95% of say the UK, will have IQs within 15.5 points of the PGS prediction.

So if you have a PGS of +2 SD that correlates 0.85 with IQ, your IQ will likely be 0.85(2) = +1.7 or IQ 126, with a 95% confidence interval of 111 to 142. But of course we’re nowhere near seeing a 0.85 correlation.

To get the general public to really trust polygenic scores for IQ, I’d guess the accuracy would have to be within 5 points of the true score. Within 10 points would lead to people who actually differ by 20 points regularly ending up with the same polygenic score. Since 20 points tend to be the difference between leaders and followers, such errors would be highly noticeable.

I think if they achieved a correlation of 0.7 with IQ they’d be considered credible (especially if the predictive power was maintained across oceans and generations). That’s the correlation between different IQ type tests with each-other and these are routinely used to decide issues as important as who gets into an elite college, who gets excluded from the military, who gets diagnosed as disabled or gifted, and who gets sentenced to death by the courts.

By the way, what do you think about this argument against people who consider intelligence entirely environmental: If that really was the case, then disadvantaged people would NEVER be smarter than people with good backgrounds. So why even bother giving people from poor backgrounds a chance? 100% environmentalism leads to un-egalitarian conclusions, and is easily disproven by the existence of smart disadvantage people.

It’s prima facie absurd, but it wouldn’t necessarily lead to the conclusion that we shouldn’t give deprived people a chance. On the contrary it might lead to the conclusion that changing IQ is simply a matter of changing environments.

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