genomics workshop demography of aging centers biomarker network meeting in conjunction with the...

Genomics Workshop

Demography of Aging Centers Biomarker Network Meeting in Conjunction with the Annual Meeting of the PAA

April 14, 9:00 AM to 3:30 PM – Hyatt Regency, Dallas, Texas

Sponsored by USC/UCLA Center of Biodemography and Population Health

Organized by Teresa Seeman, Steven Cole, Eileen Crimmins

Tactical aspects of study administration and sample capture/storage

Biological overview of genetics & functional genomics

Strategic aspects of study design and data analysis

Lunch

Technical aspects of study design and data analysis

Perspectives on the State of the Field

Application clinic


DNA1. New sample capture

• Methods: e.g., Oragene, leukocytes• Consent & administrative issues

2. Retrospective analyses• Sources: blood spots, cheek swabs, etc• Consent & administrative issues

3. Epigenetics• DNA methylation • Histone acetylation & chromatin dynamics• Tissue specificity (vs DNA)

4. Tactical issues – Reports from the Field• I wish I’d known then…

RNA1. Identifying appropriate target tissues

• Whole blood, PBMC, saliva, hair, path specim.2. Sample capture/storage3. Consent & administrative issues

http://www.dnagenotek.com/

Gene

IL6 DNA

Gene

IL6

RNA

DNA

Gene

Health

IL6

RNA

DNA


Theoretical framework: Genes, Environments, transcription, and health

1. “Genetic” influences (missing h, penetrance R-square, etc.)

2. Functional genomics• Transcription factors• Epigenetics

3. Gene-Environment interactions• Regulatory polymorphism• Coding polymorphism

System dynamics

1. Feedback, network pleiotropy

2. Recursive developmental trajectories

Gene

IL6 DNA






System dynamics



Gene

IL6 DNA

Gene

IL6

RNA

DNA

Gene

Health

IL6

RNA

DNA

Social Environment

Gene

Health

IL6

RNA

DNA

IL6TCT TGCGATGCTA AAG

IL6 gene transcription



NE



NE

PKA



NE

GATA1P

PKA



NE

GATA1P

PKA

IL6

prom

oter

act

ivity

(f

old-

chan

ge)

10

8

6

4

2

0

Norepinephrine (M): 0 10 - 0 10

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

Non-depressedDepressed

p = .008

Socio-environmental regulation of IL6

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al






System dynamics



Gene

IL6 DNA

Gene

Health

IL6

RNA

DNA

Gene

IL6 DNA






System dynamics



Social Environment

Gene

Health

IL6

RNA

DNA

Social Environment

Gene

Health

IL6… [G/C] …

RNA

DNA

Social Environment

Gene

IL6… [G/C] … DNA


Gene x Environment Interaction

In silico


V$GATA1_01 = .943


In silico


C

V$GATA1_01 = .943


In silico


C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico

Tra

nscr

iptio

nal a

ctiv

ity

(fol

d-ch

ange

)

10

8

6

4

2

0

IL6 promoter: WT -174C



C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico In vitro

Tra

nscr

iptio

nal a

ctiv

ity

(fol

d-ch

ange

)

10

8

6

4

2

0



Difference: p < .0001


C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico In vitro

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al


p = .008


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

IL6 -174 GG IL6 -174 CC/GC

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

p = .439


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al


p = .008


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

IL6 -174 GG IL6 -174 CC/GC






System dynamics



Social Environment

Gene

Health

IL6

RNA

DNA

Social Environment

Gene

Health

IL6

RNA

DNA… [G/C] …

Social Environment

Gene

Health2

IL6

RNA2

DNA… [G/C] …






System dynamics



Social Environment

Gene

Health

IL6

RNA

DNA

Social Environment

Gene

IL6

RNA

DNA

Behavior

Social Environment

Gene

IL6

RNA

DNA

Behavior

Gene-Environment Correlation

Social Environment

Gene

IL6

RNA

DNA

Behavior

Gene-Environment Correlation

Recursive Molecular Remodeling

Body1

Recursive developmental remodeling

Cole (2009) Current Directions in Psychological Science

Environment1 Body1



Environment1 Body1

Behavior1



Environment1 Body1

RNA1

Behavior1



Time 1 Environment1 Body1

RNA1

Behavior1

Time 2 Body2




RNA1

Behavior1





RNA1

Behavior1


RNA2

Behavior2




RNA1

Behavior1


RNA2

Behavior2


RNA3

Behavior3




RNA1

Behavior1


RNA2

Behavior2


RNA3

Behavior3


RNA = intra-organismic adaptation







System dynamics




Basic substantive objectives & study designs

1. “Gene discovery” (e.g., genetic epidemiology)

2. Environmental regulation of health (via transcription)

3. Gene-Environment interaction

Gene

IL6 DNA

Gene

Health

IL6 DNA

Gene

Health

IL6

RNA

DNA

Gene

Health

IL6

RNA

DNA… [G/C] …… [G/C] …






Antagonistic pleiotropy

IL6 -174: CC GC GG CC GC GG

p = .007

Older Adult Adolescent

CR

P m

g/L

/ A

dver

sity

SD

3.0

2.0

1.0

0.0

-1.0

-2.0

-3.0

p = .032


IL6 -174: CC GC GG CC GC GG

p = .007

Older Adult Adolescent

CR

P m

g/L

/ A

dver

sity

SD

3.0

2.0

1.0

0.0

-1.0

-2.0

-3.0

p = .032


Evolution deletes disadvantage, particularly to the young

GG GC CC

Out

com

e

Fisher’s regression:

GG GC CC

Out

com

e

y = a + b(#G) + e


GG GC CC

Out

com

e

y = a + b(#G) + e

Environment A

GG GC CCO

utco

me

Environment B


GG GC CC

Out

com

e

y = a + b(#G) + c(Env) + d(#G x Env) + e

Environment A

GG GC CCO

utco

me

Environment B


GG GC CC

Out

com

e

y = a + b(#G) + e’ ← c(Env) + d(#G x Env) + e

Environment A

GG GC CCO

utco

me

Environment B


GG GC CC

Out

com

e

y = a + b(#G) + e’ ← c(Env) + d(#G x Env) + e ↓ power

Environment A

GG GC CCO

utco

me

Environment B


GG GC CC

Out

com

e

y = a + b(#G) + e’ ← c(Env) + d(#G x Env) + e ↓ power ↑ parameter estimate bias

Environment A

GG GC CCO

utco

me

Environment B


GG GC CC

Out

com

e

y = a + b(#G) + e’ ← c(Env) + d(#G x Env) + e ↓ power ↑ parameter estimate bias

Marginal: 0

Environment A

GG GC CCO

utco

me

Environment B







Valid statistical models are one major reason that substantive interests (environments) matter.







Valid statistical models are one major reason that substantive interests (environments) matter.

OK, then, let’s have lunch.


Study designs, assay technologies, and statistical methods

1. “Gene discovery” (e.g., genetic epidemiology)• Candidate gene studies• Genome-wide association studies• The bioinformatic middle road

2. Environmental regulation of health (via transcription)• Candidate transcript studies• Genome-wide approaches

3. Gene-Environment interaction• Statistical issues• Revisiting the bioinformatic middle road



1. “Gene discovery” (e.g., genetic epidemiology)• Candidate gene studies

- Candidate identification- Targeted genotyping

a. PCRb. High-throughput approaches

- Statistical modelsa. Fisher’s basic regression modelb. Multivariate mapping / association / recombination

i. Recombinationii. Haplotype blocks

c. Confoundingi. Linkage disequilibrium & haplotype analysesii. Ethnic stratification

Phenotypic ascertainmentGenetic ancestry

iii. Mendelian randomization


C


C

V$GATA1_01 = .943


In silico


C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico

Tra

nscr

iptio

nal a

ctiv

ity

(fol

d-ch

ange

)

10

8

6

4

2

0





C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico In vitro

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

p = .439


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al


p = .008


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

IL6 -174 GG IL6 -174 CC/GC

Well ID1 ID2 RFU1 RFU2 Ct1 Ct2 CallA01 053 053 1094.39 956.90 42.53 41.36 HeterozygoteA02 065 065 -43.33 1519.25 60.00 40.39 Allele2A03 075 075 1126.77 890.96 42.82 42.02 HeterozygoteA04 079 079 2095.09 25.36 42.84 60.00 Allele1A05 087 087 2187.80 18.09 41.27 60.00 Allele1


GG GC CC

Out

com

e


GG GC CC

Out

com

e

y = a + b(#G)


GG GC CC

Out

com

e

y = a + b(#G)

y = a + b(GG) + c(GC) + d(CC)

http://www.biomedcentral.com/1471-2105/9/44/figure/F4


GG GC CC

Out

com

e

y = a + b(#G rs1800795)


GG GC CC

Out

com

e

y = a + b(#G rs1800795)

y = a + b(#G rs1800795) + c(#T rs20937) + ….


GG GC CC

Out

com

e

y = a + b(#G rs1800795)

y = a + b(Haplotype containing rs1800795)


GG GC CC

Out

com

e

y = a + b(#G rs1800795)

y = a + b(Haplotype containing rs1800795)y = a + b(ATTCGTAC)


GG GC CC

Out

com

e

y = a + b(#G rs1800795)

y = a + b(Haplotype containing rs1800795)y = a + b(ATTCGTAC)

HapMap Tag SNP

Linkage-driven indirect association gradients

Culture/behavior/exposure“Environment”

http://i38.tinypic.com/erhhc0.jpg

Ancestry classification via mitochondrial haplogroups (also Y haplogroups for paternal lineage)

CRP

CVD

CRP

CVDCRP

CRP

CVDCRP

IL-6



1. “Gene discovery” (e.g., genetic epidemiology)• Candidate gene studies• Genome-wide association studies




- Marker selection for blind search: tag SNPs- Massively parallel genotyping

a. Array-based strategiesb. Deep resequencing

- Statistical modelsa. Main effect modelsb. Interaction modelsc. Managing Type I error

- Bonferronni & FDR- Internal cross-validation- External replication

http://images.google.com/imgres?imgurl=http://www.nature.com/nature/journal/v444/n7117/images/444256a-i1.0.jpg&imgrefurl=http://www.nature.com/uidfinder/10.1038/444256a&usg=___Hu5MCWPRD6v4BmpteEvwpcY9s0=&h=400&w=400&sz=51&hl=en&start=1&itbs=1&tbnid=5oBKu71P1R_FaM:&tbnh=124&tbnw=124&prev=/images%3Fq%3Dillumina%2Bbead%26hl%3Den%26gbv%3D2%26tbs%3Disch:1


GG GC CC

Out

com

e

y = a + b(#G)

y = a + b(GG) + c(GC) + d(CC)


GG GC CC

Out

com

e

Environment A

GG GC CCO

utco

me

Environment B

y = a + b(#G)

y = a + b(GG) + c(GC) + d(CC)


GG GC CC

Out

com

e

y = a + b(#G) + c(Env) + d(#G x Env)

y = a + b(GG) + c(GC) + d(CC) + e(Env) + f(Env x GG) + g(Env x GC) + h(Env x CC)

Environment A

GG GC CCO

utco

me

Environment B

Type 1 / false positive error:


Confirmatory hypothesis testing (candidate genes)

1 hypothesis = 1 t-test = 1 p-value = no problem: p < .05 = p < .05




Gene mapping (exploratory association testing)

Gene expression: 22,000 p-values = 1,100 false positives (p < .05)p(false discovery > 0) = .999999999999999999999999+




Gene mapping (exploratory association testing)

Gene expression: 22,000 p-values = 1,100 false positives (p < .05)p(false discovery > 0) = .999999999999999999999999+

Gene polymorphism: 10,000,000 p-values = 500,000 false positives (p < .05)p(false discovery > 0) = .999999999999999999999999+

What to do?

What to do?

1. Increase stringency (intra-study)

Bonferroni correct ( p = .05/22,000 = .00000227 )Choice: huge samples or massive Type 2 “false negative” error

What to do?



Model/simulate errorRandomization test or FDR modeling = less conservative bias

Unimpressive yield: p = .00000300 if you’re lucky. Still too conservative, and biased ( omitted true effects in error term )

What to do?





Use a better sampling design

0 5000 10000 15000 20000

0.0

0.2

0.4

0.6

0.8

1.0

sample size

po

we

r

Population prevalence design

0 5000 10000 15000 20000

0.0

0.2

0.4

0.6

0.8

1.0

sample size

po

we

r

0 500 1000 1500 2000

0.0

0.2

0.4

0.6

0.8

1.0

sample sizep

ow

er

Population prevalence design Outcome-stratified design

What to do?






What to do?






2. Replicate (inter-study or intra-study cross-validation)

.05 x .05 x .05 = .000125 x 22,000 = 2.75 false positives ( vs. 1,100 )

What to do?






2. Replicate (inter-study or intra-study crossvalidation)

.05 x .05 x .05 = .000125 x 22,000 = 2.75 false positives ( vs. 1,100 )



1. “Gene discovery” (e.g., genetic epidemiology)• Candidate gene studies• Genome-wide association studies• The bioinformatic “middle road” – biological hypotheses buy power




- Candidate set selectiona. Regulatory polymorphismb. Coding polymorphism

- Statistical considerationsa. Powerb. Differential enrichment


In silico prediction of Gene x Environment Interaction


C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico

Tra

nscr

iptio

nal a

ctiv

ity

(fol

d-ch

ange

)

10

8

6

4

2

0





C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico In vitro

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

p = .439


70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al


p = .008

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

70 80 90

0.0

0.2

0.4

0.6

0.8

1.0

Age

Su

rviv

al

IL6 -174 GG IL6 -174 CC/GC


In vivo

FLJ20719 -734LOC148490 -929AKR7A2 -678RHCE -292RHCE -292RHCE -292RHCE -292LOC440576 -934SOC -39SOC -49SOC -26UNQ6122 -877LAPTM5 -728PHC2 -168PHC2 -16ITGB3BP -311FLJ20331 -994ZNF265 -663ZNF265 -663FUBP1 -778LOC388650 -392LOC388654 -957PDE4DIP -175COAS2 -435LOC199882 -474LOC440689 -692LOC440689 -16LOC441906 -496FLG -17LEP3 -631RAB13 -310LOC91181 -956LOC91181 -956LOC126669 -407LOC440693 -399PKLR -118PKLR -597FCRH1 -580SPTA1 -163SLAMF9 -256KCNJ10 -383ITLN1 -760ITLN1 -760F11R -798F11R -798LMX1A -85SELP -144LOC400796 -263F13B -881F13B -881MYOG -951LOC440712 -956LGTN -331FLJ10874 -676GPATC2 -556LOC440721 -625AGT 1FLJ10359 -367LOC441927 -406LOC440741 -564MGC12466 -863KIAA1720 -894LOC388578 -522LOC391205 -430MIG-6 -618MIG-6 -638MIG-6 -678LOC441870 -731LOC440561 -255LOC401940 -500LOC401940 -564LOC401940 -606LOC339553 -400LOC440753 -695LOC388789 -593FLJ38374 -686LOC391241 -81LOC388794 -28C20orf70 -431STK4 -122PIGT -910DNTTIP1 -479C20orf67 -1MMP9 -875CEBPB -978RNPC1 -370RNPC1 -370TH1L -26TH1L -26LOC400849 -714LOC400849 -382CGI-09 -309FKHL18 -608C20orf172 -118TGM2 -220TGM2 -220LOC388798 -828Kua-UEV -465Kua-UEV -561Kua -465BTBD4 -590C21orf99 -772C21orf99 -13KRTAP15-1 -566B3GALT5 -889B3GALT5 -889B3GALT5 -889B3GALT5 -889B3GALT5 -889LOC441955 -824LOC441955 -824LOC400858 -624CLDN8 -17KRTAP19-7 -127DSCR1 -620C21orf84 -232KRTAP12-4 -899FTCD -410FTCD -410LOC440842 -24PEX26 -129PEX26 -89ZNF74 -726ZNF74 -726LOC440804 -940SMARCB1 -290CABIN1 -797KIAA1671 -26ARP10 -612ADSL -602ARHGAP8 -260NUP50 -629PPARA -184PPARA -184

BID -126DGCR14 -951TXNRD2 -882LOC391303 -881LOC150221 -939LOC91219 -352LOC150236 -666GSTT1 -141SEC14L4 -746SSTR3 -705FLJ22582 -372DIA1 -749ATP5L2 -328A4GALT -825SULT4A1 -729SULT4A1 -729C2orf15 -882LOC129521 -477LOC440892 -918IL1RL1 -332MRPS9 -970LOC442037 -839IL1F7 -978IL1F7 -978IL1F7 -978IL1F7 -978MGC52000 -273MGC52000 -466MGC52057 -404MAP1D -120COL3A1 -310SLC39A10 -921LOC200726 -220IL8RB -447TUBA4 -643FLJ25955 -24ALPPL2 -296UGT1A9 -651UGT1A7 -351UGT1A6 -224UGT1A6 -402TRPM8 -170ASB1 -723GCKR -204LOC388938 -212FLJ38348 -606MSH2 -376MSH2 -976MSH2 -376MSH2 -376SBLF -59LOC151443 -85LOC391387 -134SEMA4F -751RBM29 -1LOC339562 -621LOC339562 -641LOC200493 -245TXNDC9 -714FLJ40629 -946LOC401005 -12LOC389050 -170ORC4L -16ORC4L -16ORC4L -16ORC4L -16ARL5 -895ARL5 -895NR4A2 -527NR4A2 -527NR4A2 -527NR4A2 -527ATP5G3 -55ZNF533 -598ZSWIM2 -772PGAP1 -821PGAP1 -827SF3B1 -138ORC2L -786LOC391475 -413CRYGC -765PECR -942SLC23A3 -412LOC442070 -877LOC129607 -488LOC339789 -268LOC130502 -558ALK -710BCL11A -615BCL11A -615BCL11A -615BCL11A -615PAP -438PAP -438PAP -531CNTN4 -809PPARG -584PPARG -914LOC401054 -926GALNTL2 -427FBXL2 -107APRG1 -269APRG1 -347LOC440951 -20LOC389123 -140LOC285194 -808NR1I2 -769STXBP5L -480LOC442092 -880MRPS22 -897KCNAB1 -793LOC402146 -134LOC90133 -2NLGN1 -541FLJ20522 -803ATP2B2 -593LOC440946 -917ANKRD28 -437LOC152024 -365FLJ32685 -953SLC4A7 -509MST1 -895LOC377064 -623LOC200959 -572CPOX -150LOC401079 -259CBLB -250LOC344807 -514GPR156 -497IQCB1 -412MGC34728 -553LOC256374 -248KIAA0861 -435MGC15397 -397LOC254808 -484

LRRC15 -288KIAA0226 -776LOC255324 -380IBSP -319MGC48628 -101NDST3 -902LOC401149 -733LOC441038 -837FLJ35630 -291CYP4V2 -117LOC401164 -978LOC391727 -934LOC399917 -840ZAR1 -106LOC401132 -18PF4 -819EIF4E -716ADH7 -557TACR3 -957AGXT2L1 -631PLA2G12A -795PITX2 -411PITX2 -411LOC401155 -72CDHJ -652FGA -110FGA -110PPID -384LOC441049 -368GPM6A -203LOC389833 -878LOC389833 -288LOC389833 -288LOC389833 -878LOC442102 -418FGFBP1 -290LOC441013 -188FLJ00310 -289FLJ00310 -881FLJ00310 -289FLJ00310 -289FLJ00310 -289FLJ00310 -289FLJ00310 -289LOC442127 -287SRD5A1 -631LOC345711 -877LOC389281 -225MGC42105 -669PELO -938BDP1 -918DKFZp564C0469 -378LOC134505 -63TSLP -331LOC340069 -755SNCAIP -671LOC441106 -646SLC27A6 -484CDC42SE2 -384PHF15 -52LOC389331 -27PCDHA4 -26PCDHA4 -26PCDHB3 -623PCDHB6 -212PCDHB16 -609ABLIM3 -474LARP -716LOC134541 -868FGFR4 -472FGFR4 -472FGFR4 -745FGFR4 -745LOC442145 -7LOC442146 -856LOC345462 -604LOC345462 -609LOC442148 -595OR2V2 -340OR2V2 -901TPPP -454MYO10 -583LOC441066 -463GDNF -36LOC345643 -568FOXD1 -990ARSB -493DHFR -473SPATA9 -748CHD1 -581STK22D -863LOC389316 -227CDO1 -360FLJ33977 -166LOC391824 -129ALDH7A1 -920CAMK2A -429CAMK2A -429C5orf4 -657LOC345430 -332DUSP1 -361LOC285770 -132NQO2 -705MRS2L -22HIST1H2BA -960HIST1H2BD -597HIST1H2BD -597HIST1H2BH -618HIST1H4I -283HLA-H -477MRPS18B -207LOC401250 -26LOC401250 -497NFKBIL1 -305LY6G5B -359C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413HSPA1B -942C2 -687HLA-DRA -774HLA-DQA1 -265ZBTB9 -229LOC389386 -725TLT4 -607C6orf139 -788KIAA1411 -549C6orf57 -986C6orf165 -728POU3F2 -997LOC340148 -581

C6orf55 -149LOC345829 -202LOC442278 -732LOC442279 -858LOC401289 -82LOC285766 -472SERPINB6 -657OFCC1 -367LOC441129 -714SMA3 -762LOC222699 -719LOC441138 -870OR12D3 -872LOC346171 -389HCG4P6 -80HCG4P6 -501PSORS1C2 -78PSORS1C2 -78HLA-C -512HLA-B -594HLA-DRB1 -469HLA-DRB1 -821HLA-DQB2 0HLA-DQB2 -333HLA-DQB2 0HLA-DOB -500MLN -740LRFN2 -452C6orf108 -907C6orf108 -907PLA2G7 -227CRISP1 -236CRISP1 -236IL17F -733HMGCLL1 -759LOC442226 -67C6orf66 -832DJ467N11.1 -34RTN4IP1 -207SLC22A16 -869LOC442254 -307DEADC1 -509FLJ44955 -391SYNE1 -484SYNE1 -126LOC389435 -451LOC389435 -565PIP3-E -457T -9T -3LOC442280 -112DKFZP434J154 -615LOC401303 -632LOC441198 -739GHRHR -646ADCYAP1R1 -60C7orf16 -842LOC441209 -41GPR154 -435GPR154 -435C7orf36 -707BLVRA -400BLVRA -400LOC51619 -311WBSCR19 -38LOC136288 -523LOC392030 -632FZD9 -485LOC85865 -255LOC442341 -390AKR1D1 -159LOC93432 -126OR2F1 -160OR2A5 -927LOC441184 -336LOC441186 -584LOC441187 -654LOC389831 -914LOC389831 -914LOC222967 -338LOC222967 -338LOC340267 -244ICA1 -699AGR2 -65LOC389472 -184LOC401316 -837CRHR2 -610PDE1C -20LOC441210 -361LOC222052 -77LOC441224 -287LOC441230 -143LOC441245 -127LOC441259 -954CCL26 -441SEMA3C -385C7orf23 -761PON1 -785GATS -36ACHE -715ACHE -224ACHE -715ACHE -224ORC5L -990ORC5L -990CHCHD3 -793MGC5242 -861LOC392997 -596LOC392997 -596FLJ44186 -168HIPK2 -70ZC3HDC1 -407LOC402301 -14BAGE4 -100BAGE4 -648MCPH1 -520MCPH1 -203AMAC -766NEIL2 -956NEF3 -789PNOC -756LOC441344 -308FKSG2 -72DKFZp586M1819 -469SNTG1 -463LOC389657 -899ADHFE1 -54SULF1 -522WWP1 -695LOC401471 -326FLJ45248 -290LOC441309 -343LOC392169 -927ANGPT2 -895SPAG11 -971

SPAG11 -971SPAG11 -971SPAG11 -971SPAG11 -622SPAG11 -622SPAG11 -971DEFB104 -132LOC389633 -370ASAH1 -702ASAH1 -882FLJ22494 -242FLJ22494 -781SNAI2 -728CPA6 -613FSBP -393MFTC -905MRPL13 -525LOC442399 -126TOP1MT -477LOC286126 -887LOC340393 -922DOCK8 -109LOC441386 -327C9orf93 -708SH3GL2 -702C9orf94 -376LOC340501 -32LOC441417 -394DKFZP434M131 -944SECISBP2 -404LOC441453 -821PHF2 -646PHF2 -648LOC441457 -742LOC441457 -802PRG-3 -971RAD23B -998SLC31A2 -380OR1N2 -646C9orf54 -2C9orf54 -2LAMC3 -895LOC441473 -825LOC441473 -825LOC441473 -825DBH -768OBP2A -732EGFL7 -330EGFL7 -335TRAF2 -32LOC441408 -394LOC389702 -288C9orf46 -353SLC24A2 -265IFNA10 -138IFNA14 -85C9orf11 -311C9orf24 -905C9orf24 -905UNQ470 -31STOML2 -420LOC392334 -904LOC286327 -215HNRPK -86LOC441452 -955DIRAS2 -896LOC286359 -774TXNDC4 -690TXN -239OR1L8 -459DYT1 -561ABO -790ABO -789ABO -790XPMC2H -374LOC441474 -921LOC389734 -489LOC389734 -223FCN1 -673FCN1 -709LOC441410 -990GAGE1 -21RRAGB -788RRAGB -788LOC340527 -194SH3BGRL -944DIAPH2 -921DIAPH2 -921HSU24186 -145NXF2 -89PLP1 -918PLP1 -918LOC286436 -713SLC6A14 -962LOC392529 -73FLJ25735 -992MAGEB4 -834MAGEB4 -834LOC389844 -822LOC389844 -814UBE1 -964LOC203604 -16LOC441481 -796DMD -923RPGR 3ZNF21 -828PRKY -308LOC441537 -223LOC441539 -222LOC441535 -225LOC441536 -223LOC338588 -51UCN3 -368NET1 -14MAPK8 -856MAPK8 -856MAPK8 -856MAPK8 -856LOC399768 -100CDC2 -415SLC29A3 -596LOC143244 -131LOC439994 -962LIPL3 -68LIPL3 -704LOC439996 -302LOC387701 -717LOC387701 -817FRAT1 -287FRAT1 -287ABCC2 -3ABCC2 -3HPS6 -237NFKB2 -790PNLIPRP2 -442

DMBT1 -462DMBT1 -462DMBT1 -462FANK1 3TAF3 -544LOC441547 9LOC220998 -941TPRT -277C10orf68 -817C10orf9 -269ZNF33A -477ZNF33A -477LOC399744 -202LOC399744 -202PPYR1 -81PPYR1 -81LOC439946 -71AKR1C2 -641AKR1C2 -641LOC441560 -504LOC439975 -618NEUROG3 6AMID -452PPP3CB -854LOC439983 -240LOC389988 -68MMS19L -221C10orf69 -121GPR10 -555C10orf93 -42ASB13 -506IL15RA -222IL15RA -827USP6NL -573C10orf45 -181NMT2 -912SIAT8F -676NEBL -727C10orf52 -163LOC439953 -879LOC399737 -608CTGLF1 -504LOC439963 -500KCNQ1 -40LOC387746 -61OR51F2 -640TRIM34 -105OR10A2 -851SAA1 -721SAA1 -722LOC441593 -126PDHX -845TRIM44 -24LOC90139 -660NDUFS3 -929LOC196346 -885OR5T3 -97CTNND1 -133CTNND1 -116CNTF -149ROM1 -515MARK2 -375MARK2 -375RAB1B -75GSTP1 -841GSTP1 -841LOC440056 -824USP35 -148LOC390231 -471OR4D5 -465OR8G5 -809MGC39545 -867LOC399969 -328LOC219797 -216NUP98 -651NUP98 -651NUP98 -651NUP98 -651KIAA0409 -533LOC283299 -427LOC440026 -69LOC440030 -675LOC387754 -159LOC144100 -631HPS5 -917HPS5 -917HPS5 -917LOC387764 -149LOC440041 -221FLJ31393 -362OR8H1 -161AGTRL1 -809PRG2 -899TCN1 -716RAB3IL1 -976KIAA0404 -771CHRDL2 -754KCTD14 -94MRE11A -879MRE11A -982MMP7 -853CRYAB -175ZNF202 -527LOC387820 -553LOC387823 -178CCND2 -350NDUFA9 -485KCNA5 -805FLJ10665 -245FLJ10665 -576LOC285407 -743LOC390299 -771FLJ10652 -491LOC144245 -455PFKM -838DKFZp686O1689 -733C12orf10 -110DGKA -806DGKA -800SUOX -384ZNFN1A4 -874LYZ -944GAS41 -166VEZATIN -34LOC387876 -110C12orf8 -840COX6A1 -124LOC390364 -971LOC390364 -971LOC144678 -418LOC338797 -31SLC6A13 -445NRIP2 -107NOL1 -122LOC387701 -817FRAT1 -287FRAT1 -287ABCC2 -3ABCC2 -3HPS6 -237NFKB2 -790PNLIPRP2 -442

CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885KLRK1 -349PRB1 -589PRB1 -589PRB1 -589ADAMTS20 -965ADAMTS20 -965SLC38A2 -638K-ALPHA-1 -27KIAA1602 -262RACGAP1 -620K6IRS3 -708KRT4 -83NPFF -777STAT2 -94FLJ32949 -500IFNG -795MGC26598 -498HAL -358DKFZp434M0331 -920LOC400070 -223TSC -785GPR109B -392EPIM -568EPIM -568GALNT9 -798LOC440122 -169LOC221140 -342LOC440128 -877LOC387912 -279LOC341784 -327NURIT -947RB1 -525DKFZP434K1172 -595DKFZP434K1172 -595LOC144983 -906LOC144983 -892LOC144983 -896LOC400144 -807PROZ -865PROZ -865CRYL1 -768POSTN -32LOC440134 -367EBPL -973GUCY1B2 -832LOC338862 -918LOC404785 -818OR11H6 -269C14orf92 -234PSMA6 -219KTN1 -222C14orf166B -786EVL -28CCNB1IP1 -868CCNB1IP1 -868NEDD8 -143BAZ1A -508BAZ1A -508NFKBIA -963LOC283551 -302CDKL1 -902LOC400214 -138RTN1 -974LOC390488 -457PLEK2 -465PIGH -153RDH11 -251FLJ39779 -161KIAA1509 -179SERPINA2 -559SERPINA2 -559SERPINA2 -559SERPINA9 -856LOC390529 -204LOC388073 -112LOC400307 -332LOC283694 -71LOC400320 -443FLJ35785 -414LOC440249 -92HH114 -991PLA2G4B -483CAPN3 -318CAPN3 -318CAPN3 -318LOC400368 -320SLC28A2 -275DUT -32SCG3 -739LIPC -853OSTbeta -781LOC440289 -446COMMD4 -790LOC400433 -496LOC390637 -55FLJ11175 -113LOC440224 -815LOC283804 -112CHSY1 -876LOC440315 -303LOC440315 -303LOC400470 -62LOC388076 -715LOC440250 -206LOC440255 -981FLJ20313 -236AVEN -767KIAA0377 -896FBN1 -191SPPL2A -4BCL2L10 -653LOC145780 -610BNIP2 -842BNIP2 -421RASL12 -878SNAPC5 -540BG1 -364LOC400411 -62LOC440293 -718FLJ40113 -951

IP -207TBL3 0KIAA1171 -70TNFRSF12A -968DNAJA3 -24ALG1 -464ALG1 -464FLJ12363 -773LOC92017 -711TMC7 -412MGC16824 -271RBBP6 -795RBBP6 -795RBBP6 -795ITGAX -504ERAF -510LOC388248 -649FLJ38101 -981CES4 -221MT1H -280GAN -839PLCG2 -534CDH13 -906HSBP1 -425MLYCD -917FLJ45121 -772DPEP1 -765FLJ32252 -288FLJ32252 -346MGC35212 -360FLJ25410 -280LOC400506 -715LOC94431 -77DOC2A -265LOC441761 -889LOC57019 -375ZNF319 -360DNCLI2 -857DNCLI2 -857DKFZP434A1319 -236LOC439920 -70CHST5 -601CHST5 -756LOC390748 -242DPH2L1 -42LOC388323 -892MAP2K4 -128MAP2K4 -128KRTAP4-12 -78JJAZ1 -789CCL2 -912PSMB3 -889LOC440440 -1FLJ25168 -244SP2 -57LOC388406 -800TBX4 -465DDX42 -212DDX42 -212LOC90799 -734DKFZP586L0724 -829SSTR2 -874MRPS7 -822MRPS7 -719LOC388429 -804NARF -669NARF -669GEMIN4 -911OR1D2 -376ALOX15 -267SLC16A11 -346CLECSF14 -596CLECSF14 -640FLJ40217 -393RCV1 -761CDRT1 -618NOS2A -287NOS2A -287KRT25D -828KRT12 -585HUMGT198A -797HUMGT198A -690FLJ31222 -769LOC284058 -524GIP -957LOC400619 -823UNC13D -695LOC339162 -685LOC388462 -43SEH1L -801LOC284232 -988LOC284232 -845CABLES1 -281CABYR -908CABYR -908CABYR -908CABYR -908CABYR -908DSG3 -367SLC14A1 -333DCC -386RAB27B -713ZCCHC2 -249LOC342808 -306LOC284276 -397MYOM1 -232MC2R -113LOC441817 -600KIAA1632 -405FBXO15 -123FBXO15 -192LOC390865 -489TXNL4 -33CDC34 -270GZMM -678C19orf21 -573ARID3A -913LOC126295 -456MGC39581 -37TRAPPC5 -352LOC51257 9OR7C2 -399OR10H3 -953OR10H4 -323LOC284434 -560HSPC142 -632PGLS -935LOC148206 -288ZNF431 -967CLECSF12 -885

PSMC4 -215PSMC4 -215EGLN2 -452LOC388549 -412SYNGR4 -825RPL13A -816LOC402665 -925FLJ46385 -176LOC91661 -13LAIR2 -705LAIR2 -705KIR2DL1 -763KIR3DL2 3ZNF583 -867ZNF71 -861MGC4728 -490ZNF211 -76ZNF211 -76LOC401895 -957APBA3 -13FUT5 -174TNFSF7 8SH2D3A -2738D6A -950EIF3S4 -547RAB3D -852MGC20983 -338MGC20983 -338MGC20983 -338NDUFB7 -741LOC339377 -660IL12RB1 -56IL12RB1 -56IL12RB1 -56IL12RB1 -56LOC148198 -361CEBPA -564UNQ467 -521FLJ22573 -941CLC -823DYRK1B -849DYRK1B -849DYRK1B -849PSG11 -297PSG11 -297PSG4 -299PSG4 -299PSG9 -435FLJ34222 -415ERCC2 -123DMPK -988PGLYRP1 -212LIG1 -806FLJ32926 -288CGB8 -202TEAD2 -546FLJ20643 -895LOC400712 -236SIGLEC6 -972SIGLEC6 -972SIGLEC6 -972ZNF577 -582ZNF611 -148ZNF600 -716ZNF600 -37NALP9 -489PRDM2 -762PRDM2 -762LOC400743 -400PADI1 -598FLJ44952 -494DJ462O23.2 -973PPP1R8 5PPP1R8 5PPP1R8 5ATPIF1 -766ATPIF1 -766ATPIF1 -766LOC440581 -793CGI-94 -384FLJ14351 -753UROD -715LOC441885 -810DKFZp761D221 -478DKFZp761D221 -221IL23R -322CTH -6CTH -6AK5 -966DNAJB4 -987CDC7 -604LOC388649 -426DCLRE1B -406LOC440610 -739LOC440610 -584LOC440610 -652LOC441903 -538LOC440673 -482BNIPL -420BNIPL -419SPRR1B -826SPRR1B -826IL6R -110IL6R -110CKS1B -983SYT11 -785PMF1 -223LOC164118 -75FY -397NCSTN -809HSPA6 -839HSPA6 -611CGI-01 7CGI-01 7DKFZP564J047 -208HFL1 -551HFL3 -563NEK7 -714MGC14801 -276OR2AK2 -528LOC441873 -501LOC441873 -565LOC441873 -607LOC343068 -256ARID3A -913LOC126295 -456MGC39581 -37TRAPPC5 -352LOC51257 9OR7C2 -399OR10H3 -953OR10H4 -323LOC284434 -560HSPC142 -632PGLS -935LOC148206 -288ZNF431 -967CLECSF12 -885

1205 GRE-modifying SNPs

Gene set enrichment analysis

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Outcome-stratified design

Technical take-home points:

Strengths & weaknesses of alternative approaches

1. Candidate gene studies: focus on 1 candidateAdvantages

- Scientifically tractable: incremental & cross-validatable- Maximal statistical power (focused hypothesis)

Disadvantages- Can only “discover” what we already know (i.e., biased)

2. Genome-wide association studies: focus on all candidatesAdvantages

- Unbiased de novo discoveryDisadvantages

- Minimal statistical power, particularly for interactions3. The bioinformatic “middle road”: focus on a small set of causally

plausible candidates (unbiased search of regulatory and coding SNPs) Advantages

- Scientifically tractable: “short leap of inference” & cross-validatable- Relatively high statistical power (focus on 1-10% of plausible SNPs)

Disadvantages- Likely missing some true causal genetic influences- Bioinformatically intensive – thought (and programming) required

Take-home points for this group:


1. Gene-Environment interactions are likely far more…- ubiquitous- large in effect size- clinically/socially meaningful

…than current genetic analyses presume.




There is plenty left for you to find.





2. If you have the study you have (i.e., can’t alter sampling design), your major opportunities for increasing power/discovery involve:






- focusing on substantive effects that are true/big (e.g., GxE, not G, given antagonistic pleiotropy; E, ExE, GxG,

etc.)







etc.)- modeling biological mechanisms to focus power/impose constraints (e.g., candidate systems, functional themes, regulatory themes)







etc.)- modeling biological mechanisms to focus power/impose constraints (e.g., candidate systems, functional themes, regulatory themes)- combinatorial data-mining (e.g., machine learning in discovery sample)







etc.)- modeling biological mechanisms to focus power/impose constraints (e.g., candidate systems, functional themes, regulatory themes)- combinatorial data-mining (e.g., machine learning in discovery sample)- sequential testing designs (low stringency discovery, med stringency test, high stringency confirm)








Your advantage is smart data analysis.

Follow-up references

Overview of genetics / biologyAttia, J., et al. (2009) How to use an article about genetic association: A: Background concepts. JAMA, 301, 74-81

Genetic association studiesHirschhorn, J., & Daly, M. (2005) Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics, 6, 95-108.Attia, J., et al. (2009) How to use an article about genetic association: B: Are the results of the study valid? JAMA, 301, 191-197.Cordell, H, & Clayton, D. (2005) Genetic epidemiology 3: Genetic association studies. Lancet, 366, 1121-1131

Basic statistical modeling for geneticsSiegmund, D., & Yakir, B. (2007) The statistics of gene mapping. New York, Springer

Sampling & statistical approaches for GxE discoveryThomas, D., (2010) Gene-environment-wide association studies: emerging approaches. Nature Reviews Genetics, 11, 259-272

Statistical strategies for combinatorial discoveryHastie, T., Tibshirani, R. & Friedman, J. (2001) The elements of statistical learning. New York, Springer.

.


How can we best promote the integration of genetic and demographic approaches?

Application clinic

Open microphone

1. What do you want to accomplish?

2. At what stage are you now?i. Study design?ii. Data collection?iii. Analysis and reporting?

3. How can we be of help?

Genomics Workshop








2. Environmental regulation of health (via transcription)• Candidate transcript studies

- RT-PCR- Statistical analyses incorporating temporal & spatial heterogeneity

• Genome-wide approaches- Microarrays- Theme discovery

a. Functional (Gene Ontology)b. Regulatory (TELiS)c. Spatial (SpAnGEL)

RNA

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IFN-

Antiviral cytokine mRNA

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Collado-Hidalgo et al (2006) Brain, Behavior and Immunity

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Sloan et al. (2006) Journal of VirologySloan et al. (2007) Journal of Neuroscience

Lonely

Integrated

Social isolation

J. Cacioppo

Genome Biology, 2007

78131

Palmer et al. BMC Genomics (2006)

Social Environment

Gene

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IL6

RNA

DNA

Lonely

Integrated

Social isolation

J. Cacioppo


78131

Lonely

Integrated

Social isolation

J. Cacioppo


78131

InflammationCell growth/differentiation

Transcription control

Lonely

Integrated

Social isolation

J. Cacioppo


78131

InflammationCell growth/differentiation

Transcription control

Immunoglobulin productionType I interferon antiviral response

http://www.gostat.wehi.edu.au

TRIM54ACSBG2HIST4H4KLHL32FLJ35773GPC4TRPV4LBPC20ORF200ASB15OCLM


Social Environment

Gene

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IL6

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Sp1

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NF-BEnvironment S equence ExpressionPromoterSequence

Sp1

CREB

NF-B

Sp1

CREB

NF-B

Environment S equence ExpressionPromoterSequence

?

Sp1

CREB

NF-B

Cole et al (2005) Bioinformatics, 21, 803

http://www.telis.ucla.edu

Lonely

Integrated

Social isolation

J. Cacioppo Genome Biology, 2007

78131

Lonely

Integrated

Social isolation


78131

NF-B

Lonely

Integrated

Social isolation


78131

NF-B

GRE

Social Environment

Gene

Biologicalfunction

IL6

RNA

DNA

NaB de-repression - fibroblast

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

TF3

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

TF3

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

TF3

miRNA1

miRNA2

miRNA3

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

TF3

miRNA1

miRNA2

miRNA3

DNMT1

DNMT2

DNMT3





3. Gene-Environment interaction• Statistical considerations

- Main effects and antagonistic pleiotropy- Interaction models- Combinatorial discovery

• Revisiting the “bioinformatic” middle road- Candidate set selection

a. Regulatory polymorphismb. Coding polymorphism


GG GC CC

Out

com

e

y = a + b(#G)

y = a + b(GG) + c(GC) + d(CC)


GG GC CC

Out

com

e

y = a + b(#G) + c(Env) + d(#G x Env)

y = a + b(GG) + c(GC) + d(CC) + e(Env) + f(Env x GG) + g(Env x GC) + h(Env x CC)

Environment A

GG GC CCO

utco

me

Environment B

Combinatorial explosion

107 SNPs x 101-2 environments = 108-9 intx terms

Combinatorial explosion

107 SNPs x 101-2 environments = 108-9 intx terms

N = 2,000-20,000 for current main effect studies

Given that power/effect size, need 2 Million subjects for interaction sweep.

What to do?


Bonferroni correct / FDR correctModel/simulate errorUse a better sampling design

2. Replicate (inter-study or intra-study crossvalidation)

3. Get a hypothesis- Biological- Empirical

Combinatorial discovery strategies

Smart study design + smart statistics + biological constraint

0 5000 10000 15000 20000

0.0

0.2

0.4

0.6

0.8

1.0

sample size

po

we

r

0 500 1000 1500 2000

0.0

0.2

0.4

0.6

0.8

1.0

sample sizep

ow

er




• Stratified sampling• Multi-stage testing• Cross-validation




• Data-mining / Machine learning

- CART/forests- MARS- PRIM






• Functional pathways• Regulatory pathways• Chromosomal units

Tra

nscr

iptio

nal a

ctiv

ity

(fol

d-ch

ange

)

10

8

6

4

2

0





C

V$GATA1_01 = .943

V$GATA1_01 = .619


In silico In vitro

FLJ20719 -734LOC148490 -929AKR7A2 -678RHCE -292RHCE -292RHCE -292RHCE -292LOC440576 -934SOC -39SOC -49SOC -26UNQ6122 -877LAPTM5 -728PHC2 -168PHC2 -16ITGB3BP -311FLJ20331 -994ZNF265 -663ZNF265 -663FUBP1 -778LOC388650 -392LOC388654 -957PDE4DIP -175COAS2 -435LOC199882 -474LOC440689 -692LOC440689 -16LOC441906 -496FLG -17LEP3 -631RAB13 -310LOC91181 -956LOC91181 -956LOC126669 -407LOC440693 -399PKLR -118PKLR -597FCRH1 -580SPTA1 -163SLAMF9 -256KCNJ10 -383ITLN1 -760ITLN1 -760F11R -798F11R -798LMX1A -85SELP -144LOC400796 -263F13B -881F13B -881MYOG -951LOC440712 -956LGTN -331FLJ10874 -676GPATC2 -556LOC440721 -625AGT 1FLJ10359 -367LOC441927 -406LOC440741 -564MGC12466 -863KIAA1720 -894LOC388578 -522LOC391205 -430MIG-6 -618MIG-6 -638MIG-6 -678LOC441870 -731LOC440561 -255LOC401940 -500LOC401940 -564LOC401940 -606LOC339553 -400LOC440753 -695LOC388789 -593FLJ38374 -686LOC391241 -81LOC388794 -28C20orf70 -431STK4 -122PIGT -910DNTTIP1 -479C20orf67 -1MMP9 -875CEBPB -978RNPC1 -370RNPC1 -370TH1L -26TH1L -26LOC400849 -714LOC400849 -382CGI-09 -309FKHL18 -608C20orf172 -118TGM2 -220TGM2 -220LOC388798 -828Kua-UEV -465Kua-UEV -561Kua -465BTBD4 -590C21orf99 -772C21orf99 -13KRTAP15-1 -566B3GALT5 -889B3GALT5 -889B3GALT5 -889B3GALT5 -889B3GALT5 -889LOC441955 -824LOC441955 -824LOC400858 -624CLDN8 -17KRTAP19-7 -127DSCR1 -620C21orf84 -232KRTAP12-4 -899FTCD -410FTCD -410LOC440842 -24PEX26 -129PEX26 -89ZNF74 -726ZNF74 -726LOC440804 -940SMARCB1 -290CABIN1 -797KIAA1671 -26ARP10 -612ADSL -602ARHGAP8 -260NUP50 -629PPARA -184PPARA -184

BID -126DGCR14 -951TXNRD2 -882LOC391303 -881LOC150221 -939LOC91219 -352LOC150236 -666GSTT1 -141SEC14L4 -746SSTR3 -705FLJ22582 -372DIA1 -749ATP5L2 -328A4GALT -825SULT4A1 -729SULT4A1 -729C2orf15 -882LOC129521 -477LOC440892 -918IL1RL1 -332MRPS9 -970LOC442037 -839IL1F7 -978IL1F7 -978IL1F7 -978IL1F7 -978MGC52000 -273MGC52000 -466MGC52057 -404MAP1D -120COL3A1 -310SLC39A10 -921LOC200726 -220IL8RB -447TUBA4 -643FLJ25955 -24ALPPL2 -296UGT1A9 -651UGT1A7 -351UGT1A6 -224UGT1A6 -402TRPM8 -170ASB1 -723GCKR -204LOC388938 -212FLJ38348 -606MSH2 -376MSH2 -976MSH2 -376MSH2 -376SBLF -59LOC151443 -85LOC391387 -134SEMA4F -751RBM29 -1LOC339562 -621LOC339562 -641LOC200493 -245TXNDC9 -714FLJ40629 -946LOC401005 -12LOC389050 -170ORC4L -16ORC4L -16ORC4L -16ORC4L -16ARL5 -895ARL5 -895NR4A2 -527NR4A2 -527NR4A2 -527NR4A2 -527ATP5G3 -55ZNF533 -598ZSWIM2 -772PGAP1 -821PGAP1 -827SF3B1 -138ORC2L -786LOC391475 -413CRYGC -765PECR -942SLC23A3 -412LOC442070 -877LOC129607 -488LOC339789 -268LOC130502 -558ALK -710BCL11A -615BCL11A -615BCL11A -615BCL11A -615PAP -438PAP -438PAP -531CNTN4 -809PPARG -584PPARG -914LOC401054 -926GALNTL2 -427FBXL2 -107APRG1 -269APRG1 -347LOC440951 -20LOC389123 -140LOC285194 -808NR1I2 -769STXBP5L -480LOC442092 -880MRPS22 -897KCNAB1 -793LOC402146 -134LOC90133 -2NLGN1 -541FLJ20522 -803ATP2B2 -593LOC440946 -917ANKRD28 -437LOC152024 -365FLJ32685 -953SLC4A7 -509MST1 -895LOC377064 -623LOC200959 -572CPOX -150LOC401079 -259CBLB -250LOC344807 -514GPR156 -497IQCB1 -412MGC34728 -553LOC256374 -248KIAA0861 -435MGC15397 -397LOC254808 -484

LRRC15 -288KIAA0226 -776LOC255324 -380IBSP -319MGC48628 -101NDST3 -902LOC401149 -733LOC441038 -837FLJ35630 -291CYP4V2 -117LOC401164 -978LOC391727 -934LOC399917 -840ZAR1 -106LOC401132 -18PF4 -819EIF4E -716ADH7 -557TACR3 -957AGXT2L1 -631PLA2G12A -795PITX2 -411PITX2 -411LOC401155 -72CDHJ -652FGA -110FGA -110PPID -384LOC441049 -368GPM6A -203LOC389833 -878LOC389833 -288LOC389833 -288LOC389833 -878LOC442102 -418FGFBP1 -290LOC441013 -188FLJ00310 -289FLJ00310 -881FLJ00310 -289FLJ00310 -289FLJ00310 -289FLJ00310 -289FLJ00310 -289LOC442127 -287SRD5A1 -631LOC345711 -877LOC389281 -225MGC42105 -669PELO -938BDP1 -918DKFZp564C0469 -378LOC134505 -63TSLP -331LOC340069 -755SNCAIP -671LOC441106 -646SLC27A6 -484CDC42SE2 -384PHF15 -52LOC389331 -27PCDHA4 -26PCDHA4 -26PCDHB3 -623PCDHB6 -212PCDHB16 -609ABLIM3 -474LARP -716LOC134541 -868FGFR4 -472FGFR4 -472FGFR4 -745FGFR4 -745LOC442145 -7LOC442146 -856LOC345462 -604LOC345462 -609LOC442148 -595OR2V2 -340OR2V2 -901TPPP -454MYO10 -583LOC441066 -463GDNF -36LOC345643 -568FOXD1 -990ARSB -493DHFR -473SPATA9 -748CHD1 -581STK22D -863LOC389316 -227CDO1 -360FLJ33977 -166LOC391824 -129ALDH7A1 -920CAMK2A -429CAMK2A -429C5orf4 -657LOC345430 -332DUSP1 -361LOC285770 -132NQO2 -705MRS2L -22HIST1H2BA -960HIST1H2BD -597HIST1H2BD -597HIST1H2BH -618HIST1H4I -283HLA-H -477MRPS18B -207LOC401250 -26LOC401250 -497NFKBIL1 -305LY6G5B -359C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413C6orf25 -413HSPA1B -942C2 -687HLA-DRA -774HLA-DQA1 -265ZBTB9 -229LOC389386 -725TLT4 -607C6orf139 -788KIAA1411 -549C6orf57 -986C6orf165 -728POU3F2 -997LOC340148 -581

C6orf55 -149LOC345829 -202LOC442278 -732LOC442279 -858LOC401289 -82LOC285766 -472SERPINB6 -657OFCC1 -367LOC441129 -714SMA3 -762LOC222699 -719LOC441138 -870OR12D3 -872LOC346171 -389HCG4P6 -80HCG4P6 -501PSORS1C2 -78PSORS1C2 -78HLA-C -512HLA-B -594HLA-DRB1 -469HLA-DRB1 -821HLA-DQB2 0HLA-DQB2 -333HLA-DQB2 0HLA-DOB -500MLN -740LRFN2 -452C6orf108 -907C6orf108 -907PLA2G7 -227CRISP1 -236CRISP1 -236IL17F -733HMGCLL1 -759LOC442226 -67C6orf66 -832DJ467N11.1 -34RTN4IP1 -207SLC22A16 -869LOC442254 -307DEADC1 -509FLJ44955 -391SYNE1 -484SYNE1 -126LOC389435 -451LOC389435 -565PIP3-E -457T -9T -3LOC442280 -112DKFZP434J154 -615LOC401303 -632LOC441198 -739GHRHR -646ADCYAP1R1 -60C7orf16 -842LOC441209 -41GPR154 -435GPR154 -435C7orf36 -707BLVRA -400BLVRA -400LOC51619 -311WBSCR19 -38LOC136288 -523LOC392030 -632FZD9 -485LOC85865 -255LOC442341 -390AKR1D1 -159LOC93432 -126OR2F1 -160OR2A5 -927LOC441184 -336LOC441186 -584LOC441187 -654LOC389831 -914LOC389831 -914LOC222967 -338LOC222967 -338LOC340267 -244ICA1 -699AGR2 -65LOC389472 -184LOC401316 -837CRHR2 -610PDE1C -20LOC441210 -361LOC222052 -77LOC441224 -287LOC441230 -143LOC441245 -127LOC441259 -954CCL26 -441SEMA3C -385C7orf23 -761PON1 -785GATS -36ACHE -715ACHE -224ACHE -715ACHE -224ORC5L -990ORC5L -990CHCHD3 -793MGC5242 -861LOC392997 -596LOC392997 -596FLJ44186 -168HIPK2 -70ZC3HDC1 -407LOC402301 -14BAGE4 -100BAGE4 -648MCPH1 -520MCPH1 -203AMAC -766NEIL2 -956NEF3 -789PNOC -756LOC441344 -308FKSG2 -72DKFZp586M1819 -469SNTG1 -463LOC389657 -899ADHFE1 -54SULF1 -522WWP1 -695LOC401471 -326FLJ45248 -290LOC441309 -343LOC392169 -927ANGPT2 -895SPAG11 -971

SPAG11 -971SPAG11 -971SPAG11 -971SPAG11 -622SPAG11 -622SPAG11 -971DEFB104 -132LOC389633 -370ASAH1 -702ASAH1 -882FLJ22494 -242FLJ22494 -781SNAI2 -728CPA6 -613FSBP -393MFTC -905MRPL13 -525LOC442399 -126TOP1MT -477LOC286126 -887LOC340393 -922DOCK8 -109LOC441386 -327C9orf93 -708SH3GL2 -702C9orf94 -376LOC340501 -32LOC441417 -394DKFZP434M131 -944SECISBP2 -404LOC441453 -821PHF2 -646PHF2 -648LOC441457 -742LOC441457 -802PRG-3 -971RAD23B -998SLC31A2 -380OR1N2 -646C9orf54 -2C9orf54 -2LAMC3 -895LOC441473 -825LOC441473 -825LOC441473 -825DBH -768OBP2A -732EGFL7 -330EGFL7 -335TRAF2 -32LOC441408 -394LOC389702 -288C9orf46 -353SLC24A2 -265IFNA10 -138IFNA14 -85C9orf11 -311C9orf24 -905C9orf24 -905UNQ470 -31STOML2 -420LOC392334 -904LOC286327 -215HNRPK -86LOC441452 -955DIRAS2 -896LOC286359 -774TXNDC4 -690TXN -239OR1L8 -459DYT1 -561ABO -790ABO -789ABO -790XPMC2H -374LOC441474 -921LOC389734 -489LOC389734 -223FCN1 -673FCN1 -709LOC441410 -990GAGE1 -21RRAGB -788RRAGB -788LOC340527 -194SH3BGRL -944DIAPH2 -921DIAPH2 -921HSU24186 -145NXF2 -89PLP1 -918PLP1 -918LOC286436 -713SLC6A14 -962LOC392529 -73FLJ25735 -992MAGEB4 -834MAGEB4 -834LOC389844 -822LOC389844 -814UBE1 -964LOC203604 -16LOC441481 -796DMD -923RPGR 3ZNF21 -828PRKY -308LOC441537 -223LOC441539 -222LOC441535 -225LOC441536 -223LOC338588 -51UCN3 -368NET1 -14MAPK8 -856MAPK8 -856MAPK8 -856MAPK8 -856LOC399768 -100CDC2 -415SLC29A3 -596LOC143244 -131LOC439994 -962LIPL3 -68LIPL3 -704LOC439996 -302LOC387701 -717LOC387701 -817FRAT1 -287FRAT1 -287ABCC2 -3ABCC2 -3HPS6 -237NFKB2 -790PNLIPRP2 -442

DMBT1 -462DMBT1 -462DMBT1 -462FANK1 3TAF3 -544LOC441547 9LOC220998 -941TPRT -277C10orf68 -817C10orf9 -269ZNF33A -477ZNF33A -477LOC399744 -202LOC399744 -202PPYR1 -81PPYR1 -81LOC439946 -71AKR1C2 -641AKR1C2 -641LOC441560 -504LOC439975 -618NEUROG3 6AMID -452PPP3CB -854LOC439983 -240LOC389988 -68MMS19L -221C10orf69 -121GPR10 -555C10orf93 -42ASB13 -506IL15RA -222IL15RA -827USP6NL -573C10orf45 -181NMT2 -912SIAT8F -676NEBL -727C10orf52 -163LOC439953 -879LOC399737 -608CTGLF1 -504LOC439963 -500KCNQ1 -40LOC387746 -61OR51F2 -640TRIM34 -105OR10A2 -851SAA1 -721SAA1 -722LOC441593 -126PDHX -845TRIM44 -24LOC90139 -660NDUFS3 -929LOC196346 -885OR5T3 -97CTNND1 -133CTNND1 -116CNTF -149ROM1 -515MARK2 -375MARK2 -375RAB1B -75GSTP1 -841GSTP1 -841LOC440056 -824USP35 -148LOC390231 -471OR4D5 -465OR8G5 -809MGC39545 -867LOC399969 -328LOC219797 -216NUP98 -651NUP98 -651NUP98 -651NUP98 -651KIAA0409 -533LOC283299 -427LOC440026 -69LOC440030 -675LOC387754 -159LOC144100 -631HPS5 -917HPS5 -917HPS5 -917LOC387764 -149LOC440041 -221FLJ31393 -362OR8H1 -161AGTRL1 -809PRG2 -899TCN1 -716RAB3IL1 -976KIAA0404 -771CHRDL2 -754KCTD14 -94MRE11A -879MRE11A -982MMP7 -853CRYAB -175ZNF202 -527LOC387820 -553LOC387823 -178CCND2 -350NDUFA9 -485KCNA5 -805FLJ10665 -245FLJ10665 -576LOC285407 -743LOC390299 -771FLJ10652 -491LOC144245 -455PFKM -838DKFZp686O1689 -733C12orf10 -110DGKA -806DGKA -800SUOX -384ZNFN1A4 -874LYZ -944GAS41 -166VEZATIN -34LOC387876 -110C12orf8 -840COX6A1 -124LOC390364 -971LOC390364 -971LOC144678 -418LOC338797 -31SLC6A13 -445NRIP2 -107NOL1 -122LOC387701 -817FRAT1 -287FRAT1 -287ABCC2 -3ABCC2 -3HPS6 -237NFKB2 -790PNLIPRP2 -442

CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885CLECSF12 -885KLRK1 -349PRB1 -589PRB1 -589PRB1 -589ADAMTS20 -965ADAMTS20 -965SLC38A2 -638K-ALPHA-1 -27KIAA1602 -262RACGAP1 -620K6IRS3 -708KRT4 -83NPFF -777STAT2 -94FLJ32949 -500IFNG -795MGC26598 -498HAL -358DKFZp434M0331 -920LOC400070 -223TSC -785GPR109B -392EPIM -568EPIM -568GALNT9 -798LOC440122 -169LOC221140 -342LOC440128 -877LOC387912 -279LOC341784 -327NURIT -947RB1 -525DKFZP434K1172 -595DKFZP434K1172 -595LOC144983 -906LOC144983 -892LOC144983 -896LOC400144 -807PROZ -865PROZ -865CRYL1 -768POSTN -32LOC440134 -367EBPL -973GUCY1B2 -832LOC338862 -918LOC404785 -818OR11H6 -269C14orf92 -234PSMA6 -219KTN1 -222C14orf166B -786EVL -28CCNB1IP1 -868CCNB1IP1 -868NEDD8 -143BAZ1A -508BAZ1A -508NFKBIA -963LOC283551 -302CDKL1 -902LOC400214 -138RTN1 -974LOC390488 -457PLEK2 -465PIGH -153RDH11 -251FLJ39779 -161KIAA1509 -179SERPINA2 -559SERPINA2 -559SERPINA2 -559SERPINA9 -856LOC390529 -204LOC388073 -112LOC400307 -332LOC283694 -71LOC400320 -443FLJ35785 -414LOC440249 -92HH114 -991PLA2G4B -483CAPN3 -318CAPN3 -318CAPN3 -318LOC400368 -320SLC28A2 -275DUT -32SCG3 -739LIPC -853OSTbeta -781LOC440289 -446COMMD4 -790LOC400433 -496LOC390637 -55FLJ11175 -113LOC440224 -815LOC283804 -112CHSY1 -876LOC440315 -303LOC440315 -303LOC400470 -62LOC388076 -715LOC440250 -206LOC440255 -981FLJ20313 -236AVEN -767KIAA0377 -896FBN1 -191SPPL2A -4BCL2L10 -653LOC145780 -610BNIP2 -842BNIP2 -421RASL12 -878SNAPC5 -540BG1 -364LOC400411 -62LOC440293 -718FLJ40113 -951

IP -207TBL3 0KIAA1171 -70TNFRSF12A -968DNAJA3 -24ALG1 -464ALG1 -464FLJ12363 -773LOC92017 -711TMC7 -412MGC16824 -271RBBP6 -795RBBP6 -795RBBP6 -795ITGAX -504ERAF -510LOC388248 -649FLJ38101 -981CES4 -221MT1H -280GAN -839PLCG2 -534CDH13 -906HSBP1 -425MLYCD -917FLJ45121 -772DPEP1 -765FLJ32252 -288FLJ32252 -346MGC35212 -360FLJ25410 -280LOC400506 -715LOC94431 -77DOC2A -265LOC441761 -889LOC57019 -375ZNF319 -360DNCLI2 -857DNCLI2 -857DKFZP434A1319 -236LOC439920 -70CHST5 -601CHST5 -756LOC390748 -242DPH2L1 -42LOC388323 -892MAP2K4 -128MAP2K4 -128KRTAP4-12 -78JJAZ1 -789CCL2 -912PSMB3 -889LOC440440 -1FLJ25168 -244SP2 -57LOC388406 -800TBX4 -465DDX42 -212DDX42 -212LOC90799 -734DKFZP586L0724 -829SSTR2 -874MRPS7 -822MRPS7 -719LOC388429 -804NARF -669NARF -669GEMIN4 -911OR1D2 -376ALOX15 -267SLC16A11 -346CLECSF14 -596CLECSF14 -640FLJ40217 -393RCV1 -761CDRT1 -618NOS2A -287NOS2A -287KRT25D -828KRT12 -585HUMGT198A -797HUMGT198A -690FLJ31222 -769LOC284058 -524GIP -957LOC400619 -823UNC13D -695LOC339162 -685LOC388462 -43SEH1L -801LOC284232 -988LOC284232 -845CABLES1 -281CABYR -908CABYR -908CABYR -908CABYR -908CABYR -908DSG3 -367SLC14A1 -333DCC -386RAB27B -713ZCCHC2 -249LOC342808 -306LOC284276 -397MYOM1 -232MC2R -113LOC441817 -600KIAA1632 -405FBXO15 -123FBXO15 -192LOC390865 -489TXNL4 -33CDC34 -270GZMM -678C19orf21 -573ARID3A -913LOC126295 -456MGC39581 -37TRAPPC5 -352LOC51257 9OR7C2 -399OR10H3 -953OR10H4 -323LOC284434 -560HSPC142 -632PGLS -935LOC148206 -288ZNF431 -967CLECSF12 -885

PSMC4 -215PSMC4 -215EGLN2 -452LOC388549 -412SYNGR4 -825RPL13A -816LOC402665 -925FLJ46385 -176LOC91661 -13LAIR2 -705LAIR2 -705KIR2DL1 -763KIR3DL2 3ZNF583 -867ZNF71 -861MGC4728 -490ZNF211 -76ZNF211 -76LOC401895 -957APBA3 -13FUT5 -174TNFSF7 8SH2D3A -2738D6A -950EIF3S4 -547RAB3D -852MGC20983 -338MGC20983 -338MGC20983 -338NDUFB7 -741LOC339377 -660IL12RB1 -56IL12RB1 -56IL12RB1 -56IL12RB1 -56LOC148198 -361CEBPA -564UNQ467 -521FLJ22573 -941CLC -823DYRK1B -849DYRK1B -849DYRK1B -849PSG11 -297PSG11 -297PSG4 -299PSG4 -299PSG9 -435FLJ34222 -415ERCC2 -123DMPK -988PGLYRP1 -212LIG1 -806FLJ32926 -288CGB8 -202TEAD2 -546FLJ20643 -895LOC400712 -236SIGLEC6 -972SIGLEC6 -972SIGLEC6 -972ZNF577 -582ZNF611 -148ZNF600 -716ZNF600 -37NALP9 -489PRDM2 -762PRDM2 -762LOC400743 -400PADI1 -598FLJ44952 -494DJ462O23.2 -973PPP1R8 5PPP1R8 5PPP1R8 5ATPIF1 -766ATPIF1 -766ATPIF1 -766LOC440581 -793CGI-94 -384FLJ14351 -753UROD -715LOC441885 -810DKFZp761D221 -478DKFZp761D221 -221IL23R -322CTH -6CTH -6AK5 -966DNAJB4 -987CDC7 -604LOC388649 -426DCLRE1B -406LOC440610 -739LOC440610 -584LOC440610 -652LOC441903 -538LOC440673 -482BNIPL -420BNIPL -419SPRR1B -826SPRR1B -826IL6R -110IL6R -110CKS1B -983SYT11 -785PMF1 -223LOC164118 -75FY -397NCSTN -809HSPA6 -839HSPA6 -611CGI-01 7CGI-01 7DKFZP564J047 -208HFL1 -551HFL3 -563NEK7 -714MGC14801 -276OR2AK2 -528LOC441873 -501LOC441873 -565LOC441873 -607LOC343068 -256ARID3A -913LOC126295 -456MGC39581 -37TRAPPC5 -352LOC51257 9OR7C2 -399OR10H3 -953OR10H4 -323LOC284434 -560HSPC142 -632PGLS -935LOC148206 -288ZNF431 -967CLECSF12 -885

1205 GRE-modifying SNPs

0 5000 10000 15000 20000

0.0

0.2

0.4

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0.8

1.0

sample size

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we

r

0 500 1000 1500 2000

0.0

0.2

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sample sizep

ow

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GEscan GEscan

Outcome-stratified design

Coding sequence polymorphisms

gene 1

gene 2

gene 3

gene 4

gene 5

gene 6

gene 7

gene 8

gene 9

gene 10

gene 11

gene 12

gene 13

gene 14

gene 15

gene 16

gene 17

gene 18

gene 19

gene 20

gene 21

gene 22

gene 23

gene 24

gene 25

gene 26

gene 27

gene 28

gene 29

gene 30

gene 31

gene 32

gene 33

gene 34

gene 35

gene 36

gene 37

gene 38

gene 39

gene 40

gene 41

TF1

TF2

TF3







Why is this critical?








Antagonistic pleiotropy is the norm → GxE








Antagonistic pleiotropy is the norm → GxEEpistatic interaction is the norm → GxG








Antagonistic pleiotropy is the norm → GxEEpistatic interaction is the norm → GxGHigh-order interactions are likely normal → GxGxExE








Antagonistic pleiotropy is the norm → GxEEpistatic interaction is the norm → GxGHigh-order interactions are likely normal → GxGxExELow power, “replication failure”, and epistemological slop

- the missing “h”, and the missing “E”





3. Gene-Environment interaction• Statistical considerations

- Main effects and antagonistic pleiotropy- Interaction models- Combinatorial discovery

• Revisiting the “bioinformatic” middle road- Candidate set selection

a. Regulatory polymorphismb. Coding polymorphism





3. Gene-Environment interaction• Statistical considerations• Revisiting the “bioinformatic” middle road







etc.)







etc.)- modeling biological mechanisms to focus power/impose constraints (e.g., candidate systems, functional themes, regulatory themes)







etc.)- modeling biological mechanisms to focus power/impose constraints (e.g., candidate systems, functional themes, regulatory themes)- combinatorial data-mining (e.g., machine learning in discovery sample)








Your advantage is smart data analysis.

Follow-up references

Overview of genetics / biologyAttia, J., et al. (2009) How to use an article about genetic association: A: Background concepts. JAMA, 301, 74-81

Genetic association studiesHirschhorn, J., & Daly, M. (2005) Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics, 6, 95-108.Attia, J., et al. (2009) How to use an article about genetic association: B: Are the results of the study valid? JAMA, 301, 191-197.Cordell, H, & Clayton, D. (2005) Genetic epidemiology 3: Genetic association studies. Lancet, 366, 1121-1131

Basic statistical modeling for geneticsSiegmund, D., & Yakir, B. (2007) The statistics of gene mapping. New York, Springer

Sampling & statistical approaches for GxE discoveryThomas, D., (2010) Gene-environment-wide association studies: emerging approaches. Nature Reviews Genetics, 11, 259-272

Statistical strategies for combinatorial discoveryHastie, T., Tibshirani, R. & Friedman, J. (2001) The elements of statistical learning. New York, Springer.

.


How can we best promote the integration of genetic and demographic approaches?

Application clinic

Open microphone

1. What do you want to accomplish?

2. At what stage are you now?i. Study design?ii. Data collection?iii. Analysis and reporting?

3. How can we be of help?

Genomics Workshop





Richlin et al. Brain, Behavior & Immunity (2004)

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