Polygenic Risk Scores and SNP a variation in a single base pair in a DNA sequence Heritability Last five years Twin studies have mostly been done We know everything is heritable Linkage and candidate genes have shown there are not genes for anything GWAS has found a handful of tiny associations that may or may not mean anything All this about trying to translate heritability into biology causation Polygenic Risk Scores It serves as the best prediction for the trait that can be made when taking into account variation in multiple genetic variants Take the million or no SNPS order them by association w outcome and add them together then the possible scores are 0 1 or 2 weight by effect size Correlated 1 3 with behavior 5 with height retreat from biology Twins are correlated 9 for height 6 for IQ 4 for educational attainment it means that you can do genetically informed work in people without twins We could make an environmental PRS big survey data get a bunch of binary indicators of educational attainment Dunedin Study 1 037 young people from NZ followed throughout their lives PRS estimated in much larger samples then applied to smaller sample like PRS Belsky Educational Attainment r 15 Important to realize that this is a VERY small correlation But EA also correlates with Parents r 13 learning to read etc earlier higher aspirations grades more financially planful richer spouses more self control and not healthier Associated with Variance in breastfeeding smoking during pregnancy Parental smacking income television and maternal education Problems w PRS Associated with characteristics of your parents and your environment One way to get around is to study mobility how much your achievement changes from that of your parents Sibling Difference Analysis Conducted within pairs of DZ Twins randomized for PRS Between pair correlation in DZ twins r 32 within pair correlation r 13 Genome Wide Complex trait Analysis Final step away from biological action of genes A way to compute heritability without twins Remember how twin heritability works Big matrix of unrelated people Use SNP chips to establish how genetically similar they are Relation between the two is heritability No reference to action of individual genes The Missing Heritability Problem Published by Brendan Maher Science journalist not scientist Core problem in everything we ve been studying this semester Height is 90 heritable But all the GWAS genes for height together add up to maybe 5 of the variance then and 20 now Worse in behavioral sciences then and now Two Aspects for Maher Missing prediction problem twins and parents are great predictors genes not so Missing mechanism problem how do the genes when we find them actually much work to explain anything Where s the Missing Heritability Genetic structures not captured on SNP chips Copy Number Variations Rare mutations Gene Gene interactions Epigenetics New Aspect is GCTA The original MHP was about gap between heritability estimates and either prediction PRS or explanation biology GCTA allows us to compute heritability from SNPs without twins SNP heritability is lower than twin heritability So a new version of MHP is between heritability coefficients from twins and SNPs The Missing Environment Problem Remember that the same problem exists for the environment We know that Nonshared Environment accounts for a lot of variance We know that Poverty Accounts for a lot of variance Hierarchy Linear prediction higher than biological explanation because we are blindly Why is machine learning higher than linear models because we are combining Why in SNP heritability higher than prediction because we aren t predicting we combining effects of DNA even more blindly are just modeling similarity Phenotypic heritability greater than SNP heritability because relatives are REAL development not models of development Big Question 1 How Much Better Can We Get Biological explanation very difficult because of physics of carpets and inability to do experiments on humans Linear prediction models to some extent larger samples give us better models but there s a limit on how well linear models can perform as a model of real development Nonlinear prediction models Statistical and computing advances big samples but still it s a model GCTA Better chips whole genome sequencing Big Question 2 Does Prediction Equal Determination Let s say we got to the point where we could predict IQ at r 2 5 in Euro Americans Does that mean that half the variance in IQ is determined at birth Yes Prediction across groups doesn t work very well How This is Different from Eugenics 1 0 Based on in vitro fertilization embryos Would allow parents to genotype and test embryos Already used spot rare diseases Or sex Intelligence Genetics of Intelligence In many ways the core problem of any discussion of genetics and behavior Goes back to Galton The one phenotype that really matters theoretically Along with maybe schizophrenia Genetics of Intelligence Behavior genetics and intelligence have something in common Both can easily lead to racist regressive or even Nazi type outcomes This makes it tempting to dismiss them as completely false to protect progressive ideals But that s too easy We have learned that genetics of behavior does have meaning but it isn t deterministic and the concept of intelligence has meaning but it isn t a fixed human capacity Origins in Craniometry Belief that smarter people have larger heads brains than less intelligent Lots of roots in 19th Century racism There are small correlations between intelligence and head size But there could me a million reasons why Alfred Binet Started out in craniometry Wanted to measure intelligence Identify children who need special education Created first modern IQ test Mental age Validation development subtests H H Goddard Eugenicist Used Binet test to measure something called innate intelligence Coined the term moron Saw the proliferation of high grade morons as a major social issue Lewis Terman Mass marketed the Binet scales Stanford Binet Intelligence Test Still around today R M Yerkes More of a modern psychologist Developed Army alpha and beta exams for WWI Used to select for draft and assignment Then used against immigrants What is Intelligence Charles Spearman Observed that all ability tests are positively correlated with each other Factor analysis was invented to test the hypothesis that a single common factor could account for this That common factor is called g So question