Modern-day eugenics?

Journal club – eugenics and stuffMaximilian PressOctober 7, 2014 – UW Genome Sciences

Content note

• Eugenics

• Racism

• Bad science

What is eugenics?“…the science which deals with the influences that improve the inborn qualities of a race…and encourage action in the direction of perpetuating a higher racial standard.” Encyclopaedia Brittanica (1910)

“…a social philosophy advocating the improvement of human genetic traits…” Wikipedia (2014)

Early genetics ~= eugenics

wikipedia

• Francis Galton• Karl Pearson• Charles Darwin• Theodore Roosevelt• Margaret Sanger• Cold Spring Harbor

Laboratory• Alexander G. Bell• Rockefeller Foundation • Ronald A. Fisher

• Linus Pauling• John M. Keynes• Winston Churchill

International EugenicsCongress, 1921

Early genetics ~= eugenics

wikipedia

• Francis Galton• Karl Pearson• Charles Darwin• Theodore Roosevelt• Margaret Sanger• Cold Spring Harbor

Laboratory• Alexander G. Bell• Rockefeller Foundation • Ronald A. Fisher

• Linus Pauling• John M. Keynes• Winston Churchill

NOT Thomas H. Morgan

Eugenics penetrated into popular culture

Kansas exhibition 1929(?)

Eugenics had a racial, evolutionary focus

E. Haeckel (1903), Anthropogenie: oder, Entwickelungsgeschichte des Menschen

The Bell Curve: IQ and race

• Often taken to represent “intelligence” (controversial)

• Heritability: 40-80% (twin studies)

• Affected by socioeconomic/cultural factors

• Correlated with economic success

IQ is an “objective” measure that can be used to evaluate and rank people.

“…on the whole, America had already achieved enough objective equalization in its schools by 1964 so that it was hard to pick up any effects of unequal school quality.”

“It is sometimes suggested that the Black/White differential in psychometric intelligence is partly due to genetic differences (Jensen, 1972). There is not much direct evidence on this point, but what little there is fails to support the genetic hypothesis.”-American Psychological Association task force (1996)

(3 variants explain ~3 IQ points)

Bell Curve spinoffs

• Nicholas Wade, A Troublesome Inheritance (2014)

Bell Curve spinoffs

• Nicholas Wade, A Troublesome Inheritance (2014)

• Richard Lynn, The Global Bell Curve (2008)– Many societies are racially diverse, not just USA– “consistent evidence of race-based social hierarchies”

(wikipedia)

The papers today

Author Year Journal Reviewed?D. Piffer 2013 Mankind Quarterly +D. Piffer 2014 IBC +/-D. Piffer 2014 BioRxiv -

The papers today

Author Year Journal Reviewed? dataD. Piffer 2013 Mankind Quarterly + 1KG, HapMapD. Piffer 2014 IBC +/- 1KGD. Piffer 2014 BioRxiv - 1KG

The papers today

Reviewer 2: Richard Lynn, University of Ulster

Reviewer 2: Richard Lynn, University of Ulster“This is a highly innovative paper that presents novel statistical tools to detect recent polygenic selection, by using open access data sets available to everyone. I foresee fruitful developments based on the ideas presented in this paper and a cascade of publications centered on this neglected but extremely important topic.”

The papers today

Author Year Journal Reviewed? phenotypeD. Piffer 2013 Mankind Quarterly + IQD. Piffer 2014 IBC +/- heightD. Piffer 2014 BioRxiv - IQ

The papers today

Polygenic selection

Pritchard et al. 2010

Polygenic selection

Variants under a polygenic selection should be:• Correlated with each other in their allelic distribution• Correlated with the phenotype in question

Pop rs1 rs2 rs3 rs4 rs5 rs6 rs7 rs8 … rsN

Data: 1000 genomes data for 89 SNPs associated with height (Lango Allen et al. 2009) average height measurements for 14 1000 genomes populations

GWAS SNPs

Pop rs1 rs2 rs3 rs4 rs5 rs6 rs7 rs8 … rsN

CEU .32 …

YRI .49

CHB .25

Divided into 9 bins, allele frequencies

GWAS SNP frequencies

Pop rs1+2 rs3+4 rs5+6 rs7+8 rsN-1+N

CEU .32

YRI .49

CHB .25

Divided into 9 bins, allele frequencies averaged within bins for each population

GWAS SNP average frequencies

Divided into 9 bins, allele frequencies averaged within bins for each population PCA on 14 x 9 matrix of meta-allele frequencies

Pop rs1+2 rs3+4 rs5+6 rs7+8 rsN-1+N

CEU .32

YRI .49

CHB .25

GWAS SNP average frequencies

PCA for “factor” extractionSA

HOURS WORKED / WEEK

PC1: “CAPITALIST SCORE”

PC2: “LUCK”

PCA for “factor” extraction

Person Capitalism Luck

Lisa 10 -5

Frank 0 5

Erin 5 0

PC2: “LUCK”

Person Capitalism Luck Happiness

Lisa 10 -5 3

Frank 0 5 -5

Erin 5 0 1

PC2: “LUCK”

Person Capitalism Luck Happiness

Lisa 10 -5 3

Frank 0 5 -5

Erin 5 0 1

Being a capitalist (PC1) makes you happier than being lucky (PC2).

PCA to get a “polygenic score”

Allele 1 frequency

PCA to get a “polygenic score”

Allele 1 frequency

Population PC1 PC2

CEU 10 7

YRI 0 5

CHB 5 0

Go fishing for a PC correlated to height

Allele 1 frequency

Population PC1 PC2 height

CEU 10 7 180

YRI 0 5 178

CHB 5 0 170

Fishing for a ‘height’ factor

(imaginary)

(provided in paper)

r = 0.98 (? 0.84)P = 0.02 (? 6e-5)

East Asian populations

Populations of EuropeanAnd African descent

The papers today

Mankind Quarterly paper: same, but for IQ

r = 0.9P < 0.001

Populations of European descent

Populations of African descent

Admixed Latin American populations

r = 0.9P < 0.001

Populations of European descent

Populations of African descent

Admixed Latin American populations

Explanation?

What do you see (PC1 and PC2) when you do PCA on 1KG data?

1000 Genomes, Nature (2012)

(African descent vs. everyone else)

t Asia

1000 Genomes, Nature (2012) “IQ” PC1?

“Height” PC2?

So basically Piffer’s signal is all population structure?

• yes

So basically Piffer’s signal is all population structure?

• yes

This kind of thing only happens in weird, obscure journals, right?

• no

Bad genetics elsewhere

Ashraf and Galor, American Economic Review (2013)

Conclusions

• Eugenics is alive and well

Conclusions

• Ideologically motivated researchers:– read genetics literature– use openly available data– exploit modern research dissemination venues– act unethically to get papers published

Conclusions

• Ideologically motivated researchers:– read genetics literature– use openly available data– exploit modern research dissemination venues– act unethically to get papers published

• Mainstream researchers do weird things with genetic data too, they just get challenged on it

Some questions

• How do we feel about unethical researchers having access to data?

• Should genomicists do more to counter flawed analyses of genomic data?

• Is it worth paying attention to marginal research communication venues?

Some questions

Acknowledgments

Queitsch Lab

Questions or thoughts?

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