GeneEnvironment Interaction VirginiaInstitute for Psychiatric 基因的环境交互作用弗吉尼亚理工大学的精神

1、gene-environment interaction & correlationdanielle dick & tim yorkvcu workshop, fall 2010gene-environment interaction genetic control of sensitivity to the environment environmental control of gene expression bottom line: nature of genetic effects differs among environmentsstandard univariat

2、e modelp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.01.01.01.01.01.01.0aaccee p = a + c + evar(p) = a2+c2+e2contributions of genetic, shared environment, genotype x environment interaction effects to twin/sib resemblancemz pairsdz pairs/full sibsshared environment11additive genetic effects1genotype x shared

3、environment interaction1 x 1 = 11 x = contributions of genetic, shared environment, genotype x shared environment interaction effects to twin/sib resemblancemz pairsdz pairs/full sibsshared environment11additive genetic effects1genotype x shared environment interaction1 x 1 = 11 x = in other wordsif

4、 gene-(shared) environment interaction is not explicitly modeled, it will be subsumed into the a term in the classic twin model.contributions of genetic, unshared environment, genotype x unshared environment interaction effects to twin/sib resemblancemz pairsdz pairs/full sibsunshared (unique) envir

5、onment00additive genetic effects1genotype x unshared environment interaction0 x 1 = 00 x = 0if gene-(unshared) environment interaction is not explicitly modeled, it will be subsumed into the e term in the classic twin model.ways to model gene-environment interaction in twin data multiple group model

6、s (parallel to testing for sex effects using multiple groups)sex effectsp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0afafcfcfefeffemalesp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0amamcmcmememmalessex effectsp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0afafcfcfefeffemalesp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0amamcmcmememma

7、lesaf = am ? cf = cm ? ef = em ?gxe effectsp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0afafcfcfefefurbanp1p2a1a2c1c2e1e21.0 (mz) / .5 (dz)1.0amamcmcmememruralau = ar ? cu = cr ? eu = er ?practical: using multiple group models to test for gxeproblem: many environments of interest do not fall into groups reg

8、ional alcohol sales parental warmth parental monitoring socioeconomic status grouping these variables into high/low categories loses a lot of informationdefinition variables in mx general definition: definition variables are variables that may vary per subject and that are not dependent variables in

9、 mx: the specific value of the def var for a specific individual is read into a matrix in mx when analyzing the data of that particular individualdefinition variables in mx create dynamic var/cov structure common uses: 1.to model changes in variance components as function of some variable (e.g., age

10、, ses, etc)2.as covariates/effects on the means (e.g. age and sex)standard model means vector covariance matrixmm22222222ecaczaecamodel-fitting approach to gxetwin 1acetwin 2aceaceceammmmmodel-fitting approach to gxetwin 1acetwin 2acea+ xmcecea+ xmtwin 1twin 2mmmmindividual specific moderatorstwin 1

11、acetwin 2acea+ xm1cecea+ xm2twin 1twin 2mmmme x e interactionstwin 1acetwin 2acea+ xm1c+ ym1e+ zm1a+ xm2c+ ym2e+ zm2twin 1twin 2mmmm classic twin model: var (t) = a2 + c2 + e2 moderation model: var (t) = (a + xm)2 + (c + ym)2 + (e + zm)2 purcell 2002, twin researchvar (t) = (a + xm)2 + (c + ym)2 (e

12、+ zm)2 where m is the value of the moderator andsignificance of x indicates genetic moderationsignificance of y indicates common environmental moderationsignificance of z indicates unique environmental moderationbm indicates a main effect of the moderator on the meanmatrix letters as specified in mx

13、 scripttwin 1acetwin 2acea+ xm1c+ ym1e+ zm1a+ xm2c+ ym2e+ zm2mmmma +am*d1c+cm*d1e+em*d1a+am*d2e+em*d2c+cm*d2mumupractical: using definition variables to test for gxeadditional things to consider unstandardized versus standardized effectsadditional things to consider geneticcommon environmentalunique

14、 environmentaltotal varianceenvironment 1unstandardized variance60355100standardized variance0.600.350.05environment 2unstandardized variance607070200standardized variance0.300.350.05unstandardized versus standardized effectsdefinition variables in mx create dynamic var/cov structure common uses: 1.

15、to model changes in variance components as function of some variable (e.g., age, ses, etc)2.as covariates/effects on the means (e.g. age and sex)definition variables used as covariatesgeneral model with age and sex as covariates:yi = + 1(agei) + 2 (sexi) + where yi is the observed score of individua

16、l i, is the intercept or grand mean, 1 is the regression weight of age, agei is the age of individual i, 2 is the deviation of males (if sex is coded 0= female; 1=male), sexi is the sex of individual i, and is the residual that is not explained by the covariates (and can be decomposed further into a

17、ce etc). allowing for a main effect of x means vector covariance matrixiixmxm2122222222ecaczaecacommon uses of definition variables in the means model incorporating covariates (sex, age, etc) testing the effect of snps (association) in the context of gxe, controlling for rgegene-environment interact

18、ion genetic control of sensitivity to the environment environmental control of gene expressiongene-environment correlation genetic control of exposure to the environment environmental control of gene frequencythis complicates interpretation of gxe effects if there is a correlation between the modera

19、tor (environment) of interest and the outcome, and you find a gxe effect, its not clear if: the environment is moderating the effects of genes or trait-influencing genes are simply more likely to be present in that environmentadding covariates to means modeltwin 1acetwin 2aceaceceamm+ mm1mm+ mm2matrix letters as specified in mx scripttwin 1acetwin 2acea+ xm1c+ ym1e+ zm1a+ xm2c+ ym2e+ zm2mm+ mm1mm+ mm2a +am*d1c+cm*d1e+em*d1a+am*d2e+em*d2mu+b*d1c+cm*d2mu+b*d2main effects and moderating effectsways to deal with rgelimit study to moderators that arent