Wednesday, 27 April 2016

Genetics of racial differences in intelligence

 

As far as I know, nobody is funding studies of the genetics of racial differences in intelligence. Although research is being carried out on the genetics of intelligence generally, and the genetics of different racial groups generally, for some reason nobody makes the link.

An exception is Davide Piffer, who as far back as 2014 suggested a possible approach: find any of the genetic variants associated with intelligence, however weak and inconsistent they may be, and then look up the published literature to see how frequent those variants are in any racial group. If there are many such positive variants in a group they will be bright, and if there are fewer such positive variants they will be less bright.

Here is the first account I gave of Piffer’s work in 2014:

http://drjamesthompson.blogspot.co.uk/2014/05/lci14-davide-piffer-human-polygenic.html

So far, this post has drawn no comments. However, it might turn out to be a significant step forwards.

The next account was in 2015 showing the pattern based on 9 GWAS hits:

http://drjamesthompson.blogspot.co.uk/2015/09/gwas-hits-and-country-iq.html

Now, in the wake of the most recent publication by Davies 2016 which I covered in my last post

http://drjamesthompson.blogspot.co.uk/2016/04/genetics-of-mental-ability-greater-power.html

Davide Piffer has taken the data from that very paper in order to extend his work on racial differences.

Recent polygenic selection for educational attainment

The genetic variants identified by two large GWAS of educational attainment were used to test a polygenic selection model.

Average frequencies of alleles with positive (Beta) effect on the phenotype (polygenic scores) were compared across populations and racial groups using data from 1000 Genomes and ALFRED. Strong correlations between polygenic scores and population IQ were found (r>0.8). Moreover, the polygenic score obtained from the two independent GWAS exhibited a strong correlation (r= 0.83), even after pruning for linkage disequilibrium.

Factor analysis revealed that most alleles loaded on a single factor, which in turn was strongly correlated to population IQ.

Polygenic and factor scores survived control for phylogenetic autocorrelation, although the latter’s net effect on population was stronger (Betas= 0.361 and 0.861, respectively).

Results obtained from ALFRED data were similar and revealed a peak in polygenic and factor scores among East Asians (60.8% and 1.06, respectively) and a nadir among Africans and Native Americans (44.1% and 0.493).

Geographic distance from Eastern Africa (assuming an origin of modern humans there) was only weakly predictive of factor and polygenic scores (r= 0.21-0.29).

The aim of this study is to replicate the studies by Piffer (2015, 2013) that educational attainment and cognition GWAS hits have different frequencies across populations and thus, were subject to different selection pressures. To this end, the hits from the latest GWAS on educational attainment (Davies et al., 2016) will be used in the analysis. This GWAS was carried out using the UK Biobank sample (N=100K+). Over a thousand SNPs reached genome-wide significance (P< 5 x 10-8), but after controlling for linkage disequilibrium (Genotypes were LD pruned using clumping to obtain SNPs in linkage equilibrium with an r2<0.25 within a 200 bp window), a few independent signals were identified (Davies et al., 2016).

https://figshare.com/articles/Polygenic_selection_on_educational_attainment/3175522/1

The boxplot below shows the major continental groups as derived from the 1000 genomes data.

  image

 

Population

Education attainmentP.S, I.S.(Davies et al., 2016). N=14

All_Ed_Att_2016. N=942

PS All Ind. (N=16)

Factor All Ind.

IQ

Afr.Car.Barbados

0.419

0.411

0.361

-1.385726617

83

US Blacks

0.447

0.428

0.387

-1.040795929

85

Bengali Bangladesh

0.516

0.566

0.461

-0.009509494

81

Chinese Dai

0.610

0.652

0.564

1.229103674

 

Utah Whites

0.493

0.467

0.461

0.385060759

99

Chinese, Bejing

0.671

0.682

0.636

1.614207102

105

Chinese, South

0.648

0.674

0.606

1.399490512

105

Colombian

0.500

0.512

0.462

0.155020855

83.5

Esan, Nigeria

0.416

0.417

0.362

-1.517446756

71

Finland

0.560

0.560

0.524

0.873423777

101

British, GB

0.526

0.494

0.499

0.568096086

100

Gujarati Indian, Tx

0.498

0.550

0.457

0.064904594

 

Gambian

0.438

0.398

0.381

-1.3799435

62

Iberian, Spain

0.512

0.488

0.481

0.4310518

97

Indian Telegu, UK

0.510

0.583

0.457

0.030182344

 

Japan

0.652

0.679

0.625

1.422186914

105

Vietnam

0.618

0.642

0.579

1.25233893

99.4

Luhya, Kenya

0.425

0.428

0.372

-1.438642624

74

Mende, Sierra Leone

0.416

0.421

0.364

-1.40422492

64

Mexican in L.A.

0.499

0.555

0.455

0.01771732

88

Peruvian, Lima

0.477

0.559

0.430

-0.00789958

85

Punjabi, Pakistan

0.511

0.564

0.475

-0.049972973

84

Puerto Rican

0.489

0.480

0.451

0.026710407

83.5

Sri Lankan, UK

0.506

0.564

0.454

0.070996352

79

Toscani, Italy

0.501

0.486

0.458

0.265676967

99

Yoruba, Nigeria

0.421

0.417

0.372

-1.572005998

71

 

 

The analysis of independent signals from two different GWAS revealed a significant overlap across two genomic datasets. Using ALFRED and 1000 Genomes, the Rietveld et al. (2013) and Davies et al. (2016) polygenic scores were strongly correlated (r= 0.62 and 0.83, respectively). Both sets of GWAS hits were strong predictors of population IQ. The polygenic score (N=14) computed from the new independent hits (Davies et al., 2016) had a strong correlation to population IQ (r= 0.82). Similar correlation was observed for the polygenic score created by combining all the independent hits (free of LD) from the two publications (N=16): r=0.843 with population IQ.

Factor analysis produced a factor that even more strongly correlated to population IQ (r= 0.89) and survived control for spatial autocorrelation. Indeed, the predictive value of this factor was not affected by partialling out Fst distances. The high Beta value (B=0.82) and the null effect of Fst distances (B= -0.16) are suggestive of polygenic selection on these SNPs, independent of noise due to migrations or drift.

Comparisons of mean frequencies across racial groups via one-way ANOVA produced either non significant or marginally significant results, but the addition of new GWAS hits is needed to provide a definitive picture.

A limitation of this study is the reliance on GWAS hits for a complex phenotype such as educational attainment, which shares the majority of additive genetic variation with general intelligence, but also other personality and health-related traits (Krapohl et al., 2014 and 2015).

Another more obvious limitation is the small number of (independent) SNPs used for this analysis. More GWAS of intelligence or educational attainment are needed to shed light on worldwide patterns of polygenic selection on cognitive abilities.

As the author says, this can only be considered a first step. However, the method has the merit of simplicity: if some variations in the genetic code are associated with intelligence, then groups that have more of those variations ought to be more intelligent. If they are not, then the link between these variants and intelligence can be called into question. Of course, it is possible that these are not the most important variants, and that they differ between racial groups for trivial reasons. If so, then the observed associations are an unusual coincidence. I think this is a method to watch. When even more genetic signals of intelligence are identified, however weak and tentative, this approach can be put to the test, and then improved or discarded.

 

 

19 comments:

  1. Good article. I want to give kudos to Mr. Piffer for his enterprising work and his courage.

    Research on race differences is rare due to 'political' opposition by those determined to blend the races into a global soup, thereby destroying each race's genotype. The fate of James Watson is an example of what can happen to those who stray from the egalitarian/globalist orthodoxy. For those of us who believe that distinctions of our genotype are essential for maintaining distinctions of our civilization- our values and culture, and who strive to avoid what we consider an impending calamity of extinction, Mr. Piffer's work is a precious resource.

    That is, of course - Davide - as long as you continue to make the right findings. ...Sorry, just kidding there.

    ReplyDelete
  2. If lack of genome-wide statistically-significant SNPs is a problem, what happens when Piffer uses a larger set like the top 1000 hits from the full polygenic scores?

    ReplyDelete
  3. Recent studies have shown a higher Neanderthal admixture in East Asians than in Europeans.

    If Neanderthals had larger brain than Homo Sapiens, it would be interesting to investigate this contribution of admixture to genetic IQ.

    ReplyDelete
    Replies
    1. Agreed. Casts a new light on racial differences

      Delete
    2. Neanderthal brains were larger to control their larger bodies. Some brain space in neanderthals was also devoted to visual processing (They had larger eyes.), and less brain power to brain executive functions (They had a smaller prefrontal cortex.) than in Homo Sapiens (who devoted more brain power to the latter, with a larger prefrontal cortex). Otherwise, Neanderthal brains were actually smaller.
      http://www.tested.com/science/life/454072-why-bigger-neanderthal-brains-didnt-make-them-smarter-humans/
      http://humanorigins.si.edu/research/whats-hot-human-origins/neanderthals-larger-eyes-and-smaller-brains
      http://www.journals.uchicago.edu/doi/abs/10.1086/524386?journalCode=ca

      Delete
    3. edit: "Otherwise, proportionally Neanderthal brains were actually smaller."

      Delete
    4. However, when neandertal interbred with sapien, spectrum of traits would be there, the simplified extreme 2 traints
      would be a) large brain less muscular body, b) smaller (than the neandertal) brain muscular body. Evolution will
      sort out which is the fittest. A plot of the PISA maths score and neandertal-sapien introgression percentage
      from Sankararan shows a linear relationship. Brain cell function is plastic, excess brain cells can be allocated to
      function like cognition.

      #pop NeandPct PisaM12
      CHB 1.40 613 #Beijing
      JPT 1.38 536 #Japan
      CHS 1.37 561 #HK
      MXL 1.22 413 #Mexico
      FIN 1.20 519 #Finland
      CEU 1.17 506 #US white
      # 481 #US all
      # 455 #US Latino
      GBR 1.15 494 #UK
      CLM 1.14 376 #Colombia
      TSI 1.11 485 #Italy
      IBS 1.07 484 #Spain
      PUR 1.05 407 #Puerto Rico/Costa Rica
      ASW 0.34 421 #Americans of African
      LWK 0.08 388 #Kenya/Tunisia

      The relationship hold for Eurasian, for others there might be more complex interactions.

      Regression Equation for PisaMath12a:
      PisaMath12a = 113.7 * NeandPct +357.546 ; Rsq = 0.3871 ; p = 0.02316

      Regression Equation for PisaMath12e (Eurasian):
      PisaMath12e = 302 * NeandPct +152.887 ; Rsq = 0.8057 ; p = 0.002482

      dux.ie

      Delete
    5. OECD PISA maths score is used because of a 'speculative story' in the Nature Journal, "The Neanderthal correlation"
      http://www.nature.com/nature/journal/v453/n7194/full/453562a.html

      I have procrastinated about working on Sankararaman's second set of
      neanderthal introgression data which has data on many populations which do not have IQ/PISA scores. Nevertheless there are additional data points,

      PisaM12 NeandPct Pop
      521 1.076 #Estonian
      518 1.086 #Polish
      499 1.067 #Czech
      495 1.023 #French
      493 1.237 #Icelandic
      489 1.157 #Norwegian
      482 1.148 #Russian
      477 1.122 #Hungarian
      453 0.975 #Greek
      448 1.024 #Turkish
      439 1.078 #Bulgarian
      427 1.458 #Thai
      394 1.203 #Albanian
      386 0.81 #Jordanian

      There are sub-populations like Eskimo and Papuan who have higher NeandPct than the Chinese however their population numbers are small. It is noted that NeandPct for Thai is comparable to that for the Chinese and the PisaM12 is
      significantly smaller.

      dux.ie

      Delete
    6. Mexicans have a higher percentage of neanderthal ancestry, presumably due to their (E. Asian related) Amerindian ancestry (this would likely apply to other strongly Amerindian groups), and have a lower PISA score.

      Delete
    7. CORRECTION: The "speculative story" is NOT very likely given the evidence and the author is not a paleo-anthropologist, archaeologist, or human geneticist---as far as..."

      Delete
    8. (I apologize if these posts are duplicate. That was not my intention. When I posted it previously, it seemed to disappear. I have posted it again, with one correction.)
      The "speculative story" is not very likely given the evidence and the author is not a paleo-anthropologist, archaeologist, or human geneticist---as far as I know (though there may be some truth to the idea that sapiens had better social networking abilities). There is no evidence that neanderthals were more technically advanced. If any thing, the reverse is more likely. The advantages of sapiens likely included more than socially related ones.
      “The researchers found that Neanderthals that lived 25-75K years ago had a much higher proportion of their brains dedicated to visual processing, even when compared with anatomically modern humans living during the same time period. This specialization of their brains, the scientists propose, mean that less neural tissue was left over for higher-order reasoning, problem-solving and creating elaborate social networks. This would limit the Neanderthals' abilities to, for example, trade for resources not endemic to their local habitat, or in times of local scarcity. Additionally, the scientists claim, Neanderthals' ability to develop or learn new technologies could have suffered due to their brains' specialization on visual acuity.”
      http://www.popsci.com/science/article/2013-03/eyes-have-it

      Many modern behaviors are first seen in Africa:
      The oldest projectiles(though throwing spears and not yet bows) occur ca. 270,000 bc Ethiopia (likely associated with some form of early sapiens-transitional sapiens/heidelbergensis)
      http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0078092
      Evidence of arrowheads dates 60-70,000 in South Africa
      http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.466.2274&rep=rep1&type=pdf
      http://www.upi.com/Science_News/2010/08/26/Oldest-arrowheads-found-in-Africa/95431282863088/
      Middle stone age cultures of southern Africa ca 150-70,000 bc show modern behaviors , including the use of bone tools, shell beads, the trade of minerals across substantial distances ,the making of fat-based paints from ochre, seasonal fishing and shellfish, use engraved ornaments, and upper paleolithic-style stone points.
      sites; blombos, Howiesons Poort, and Pinnacle point
      e.g.:the preparation of stone for making microliths by precise heat treating to increase its flakeability at pinnacle point SA. from ca 150-70,000 bc.
      https://en.wikipedia.org/wiki/Pinnacle_Point
      https://en.wikipedia.org/wiki/Howiesons_Poort
      https://en.wikipedia.org/wiki/Blombos_Cave
      https://en.wikipedia.org/wiki/Blombos_Cave#Ochre_processing_workshop

      Delete
    9. A Howiesons Poort tradition of engraving ostrich eggshell containers dated to 60,000 years ago at Diepkloof Rock Shelter, South Africa
      http://www.pnas.org/content/107/14/6180.full
      Bone harpoons from central Africa ca. 90,000 bc.
      http://forwhattheywereweare.blogspot.com/2013/03/the-katanda-harpoons.html
      The ishango bone (a mathematical object), dates to ca 20,000 bc, in the Katanda/Semliki region
      Modernity did not diffuse north to south, nor likely did the upper paleolithic package specifically.
      The late stone age (full upper paleolithic technology) appears in South Africa at about the same time as in Eurasia(40-50,000 bc.).
      Border Cave and the beginning of the Later Stone Age in South Africa
      http://www.pnas.org/content/109/33/13208.abstract
      The proto Aurignacian-like Uluzzian and Chatelperronian cultures, previously speculatively linked to neanderthals, are now attributed to early European homo sapiens. http://forwhattheywereweare.blogspot.com/2011/11/uluzzian-was-sapiens-not-neanderthal.html
      https://en.wikipedia.org/wiki/Châtelperronian#Dispute_over_disruption_of_the_site

      Delete
    10. The aforementioned speculative story is science fiction (the occupation of the author).

      Delete
    11. edit: "Evidence of arrowheads dates at least 60-70,000 in South Africa (Seg :Sibudu and Pinnacle Point), combined with adhesives.."
      https://en.wikipedia.org/wiki/Sibudu_Cave

      Delete
  4. Piffer's most recent data is somewhat modified by (Piffer's) reanalyses which calculate somewhat higher scores for Africans in both height and iq (among other things):

    “I computed two polygenic scores (mean population frequencies): ancestral and derived. Then I created a composite score by averaging them. This gives equal weight to ancestral and derived alleles (Piffer, 2015b).The end result is that populations with higher baseline frequencies of derived alleles (such as Africans) obtain a higher score after this correction, because more weight is given to ancestral alleles.”

    “We can see that the ranking of corrected polygenic scores for height and IQ gives higher scores to Africans compared to the uncorrected scores…”

    https://topseudoscience.wordpress.com

    “Derived alleles,corrected polygenic scores and height”
    The matches between calculated iq’s and predicted ones(from psychometry) are imperfect(in the most recent re—analyses).

    In his preceding entry at “toppseudoscience” , Piffer finds that
    “A discrepancy with IQ estimates is that East Asians lag behind Europeans and that South Asians and Hispanics don’t perform better than sub-Saharan Africans, a finding that is difficult to explain at present.”

    ReplyDelete
    Replies
    1. edit: "...which calculate somewhat higher scores for Africans in both height and iq (among other findings):"

      meaning eg: perhaps calculating different scores for some groups of South Asians and Hispanics than before, not calculating higher scores for Africans on additional traits (beyond the traits of height and iq already mentioned).
      Original wording was ambiguous.

      Delete
  5. You are cited in Thilo Sarrazin's new book. I thought this may interest you, since Sarrazin will be read by a lot of people in Germany.

    ReplyDelete
    Replies
    1. Rindermann had mentioned it. However, political decisions are rarely based on facts.

      Delete
  6. A surprise from the second Sankararaman dataset is that wrt PisaM12 the effect of the percent Denisovan DNA in Sapien is more significant than that for Neandertal, i.e. on the values of Rsq, p, and the gradient of the line.

    Coefficients:
    Estimate Std. Error t value Pr(>|t|)
    (Intercept) 288.75 77.70 3.716 0.00188 **
    NeandPct 169.73 66.22 2.563 0.02084 *
    n=18; Rsq=0.2468; p=0.02084;

    Coefficients:
    Estimate Std. Error t value Pr(>|t|)
    (Intercept) 444.16 17.32 25.649 2.00e-14 ***
    DenisPct 1696.40 551.71 3.075 0.00725 **
    n=18; Rsq=0.3321; p=0.007253;

    The stepwise reduction regression drops NeandPct.

    Not much is known about the Denisovans, for example their brain size.

    dux.ie

    ReplyDelete