IBD genetics in children across diverse populations

Subra Kugathasan, MDProfessor of Pediatrics and Human Genetics

Emory University

The predictive power of genetic markers should be integrated into the management of IBD

Biology (genetics, serology andmicrobial markers vary greatly across populations

US Population at Glance

By Race:

Foreign-Born by Race:

Projected

Projected

http://www.usc.edu/schools/price/futures/pdf/2011_Pitkin-Myers_Projections-Immigrant-Generations-and-Foreign-Born.pdf

White et al., Clinical Gastroenterology and Hepatology, 2008

N=138 N=1,406

IBD phenotypes in different populationsMulti-center US populations

• Most genetic studies of IBD to date have mainly been conducted in Caucasians. Finding of Caucasians (West Europeans) cannot be extrapolated to non-Caucasians. Most results found in Caucasians do not have prognostic utility in other minority population.

• Emerging data support the hypothesis that the prevalence and disease burden among African Americans (AA) is similar to that of Caucasians.

• The disease pathogenesis, disease course and treatment responses could vary with Race/Ethnicity genetics

Why study IBD studies across populations?

CASE ENROLLMENT

CASE GOAL

CONTROL ENROLLMENT

CONTROL GOAL

0 200 400 600 800 1000 1200 1400 1600

570

105

129

133

55 150

1500

1150

Enrollment Goals and Progress to Date

Genesis AA Cohort

Previously recruited at Emory

Wisconsin Cohort

CHOP Cohort

Final Goal

• Goal: 1500 African American IBD subjects from multiple sites 1150 African American control subjects

• Detailed phenotypic characterization• Collection of whole blood for DNA and serum

NIH/NIDDK Genetic consortium – ancillary R01 Progress to data

Total CASES: 905Total CONTROLS: 238

Genesis AA Enrollment by Site

Previously recruited at Emory

Wisconsin Cohort

Emory University

University Hospitals Case Western Medical Center

University of Maryland School of Medicine

LSU Health Science Center

Children's Hospital of Philadelphia

Cincinnati Children's Hospital Medical Center

Vanderbilt-Monroe Carell Jr. Children's Hospital

UT Southwestern Children's Medical Center

UNC Chapel Hill Children's Hospital

University of Chicago Children's Hospital

Cook Children's Medical Center

Willis-Knighton Physician Network

University of Mississippi Children's Medical Center

Atlanta VA Medical Center

Montefiore Medical Center

0 20 40 60 80 100 120 140

CONTROL ENROLLMENTCASE ENROLLMENT

Ilecolonic41%

Colon52%

Ileal6%

Uppper GI1%

Disease Location

Male43%

Female57%

Gender Difference Fibrostenotic Penetrating Perianal 0%

5%

10%

15%

20%

25%

30%

25% 24%20%

Disease Behaviour

CD68%

UC28%

IBDU4%

Disease Type

IBD phenotypes in African AmericansOur current data from over 900 subjects

Age of onset among African Americans Over 900 subjects, not population based

less than 10 years

10 to 19 20 to 29 30 to 39 40 to 49 50 to 59 60 years of age and above

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

UC (%)

Crohn's (%)

Prevalence of CD and UC in the US by Age

<10 10 to 19 20 to 29 30 to 39 40 to 49 50 to 59 60 and above

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

CD (%) UC (%)

Age of Onset among Subjects AA enrolled at 18 years of age and older

<5 5 to 9 10 to 14

15 to 19

20 to 24

25 to 29

30 to 34

35 to 39

40 to 44

45 to 49

50 to 54

55 to 59

>=600

10

20

30

40

50

60

70

Crohn'sUC

Num

ber o

f Sub

ject

s Dia

gnos

ed

Why study genetics across populations?

• Non-Africans and Non Europeans represent an admixed population, with founders from West Africa and Europe.

• They have a different genetic diversity and a various lenght LD block than their founders. This makes genetic studies ideal for identifying population specific disease variants.

• It is mandatory to perform GWAS in minority population to test the hypothesis that specific disease susceptibility SNPs exist either within the known IBD loci, or in undiscovered loci.

• Most results found in Caucasians do not have prognostic utility in other minority population

Tishkoff SA et al. Science. 2009 May 22;324(5930):1035-44

AdmixtureAfrican American = 80% African + 20% Caucasian loci

Based on 1327 nuclear microsatellite and insertion/deletion markers used to asses the genetic ancestry of populations

Modified from Tishkoff SA et al. Science. 2009 May 22;324(5930):1035-44

VS. VS.

Ancestry Informative Markers can Confirm Self-reported Ethnicity

Divers et al., BMC Genet. 2011 Mar 4;12:28

4 clusters distinguishes between 4 US populations

Populations Admixture vary within the US

Modified from Tishkoff SA et al. Science. 2009 May 22;324(5930):1035-44

VS. VS.

http://en.wikipedia.org/wiki/Mexican_American

African American = 80% African + 20% Caucasian ancestry

Sister 1 84% African, 13% European

and 3% Asian

Sister 2 78% African, 18% European

and 4% Asian

http://www.taneya-kalonji.com/genblog/category/23andme/page/2

Admixture can vary between individual of the same family

Mother93% African, 6% European

and 1% Asian

African AncestryEuropean AncestryAsian AncestryNot genotyped or too little data

An admixture mapping scan is typical

Nature Reviews Genetics 6, 623-632 (August 2005)

Perc

ent A

nces

try

from

Cau

casia

n po

pula

tion

Chromosome position

Patients inherited high-risk alleles from Caucasian

High proportion of ancestry from the Caucasian population

African AncestryEuropean AncestryAsian AncestryNot genotyped or too little data

Representative AA admixture at NOD2 loci

http://blog.openhelix.eu/?p=6906

Adeyanju et al. Inflamm Bowel Dis. 2012 Dec;18(12):2357-9

Cases (n=220)

Controls (n=210)

Cases (n=40)

Controls (n=500)

Cases (n=210)

Controls (n=111)

Caucasians Africans African Americans-0.05

-4.16333634234434E-17

0.05

0.1

0.15

0.2

0.25

0.30.3

0.17

0.0025 0.0025

0.09

0.04

Alle

le F

requ

enci

es

100% European Ancestry

100% African

Ancestry80%

African Ancestry

20% European Ancestry

Adeyanju et al. Inflamm Bowel Dis. 2012 Dec;18(12):2357-9

Common NOD2 risk variants in AA with CD are due to recent Caucasian admixture

Carrier of NOD2 variants (1000fs, R702W, G908R)

First Collaborative AA Immunochip2,236 AA IBD 192,402 SNPs

1770 AA IBD 136,497 SNPs

QC filtering

 Cases + Controls

Healthy Controls

All IBD Cases

CD Cases

UC Cases

Total 1770701

(39.6%)1069

(60.4%)767

(43.3%)251

(14.2%)

Global YRI (%) 83.0 ± 8.3 82.9 ± 8.4 83.1 ± 8.2 83.2 ± 8.0 82.9 ± 8.5

Allele frequencies of Yoruba's (YRI) and Caucasians (CEU) HapMap used to estimate ancestry. Joint admixture/association tests (logistic regressions) were implemented:

1. Estimate test burdens for admixture and association mapping 2. Genotypic association stratified by local ancestry3. Combined regression coefficient in each strata and calculated pooled p-values4. Converted pooled p-values into posterior probability (pp) by using pp from admixture

mapping as prior and test burden from association mapping.

Removed SNPs with low genotyping quality or errors in duplicates/parent-offspring trios

Cedars Sinai

Emory University

John Hopkins

Second Collaborative AA Immunochip

Cedars Sinai Emory University John Hopkins TOTAL

Cases 281 746 998 2025Controls 49 283 1691 2023

TOTAL 330 1029 2689 4048

CD UC IBD-U Affected

(no disease record)

Control non-IBD

TOTAL 1472 460 80 13 1994 29

2025 Cases 2023 Controls

~ 500 pediatric cases (2 to 17 years); include ~200 early onset (2 to 10 years)

Second Collaborative AA ichip QC Process

• 4,048 Samples (2025 cases and 2023 controls)

• All genotypes jointly called with Illumina tools

• Samples with <98.5% call rate temporarily removed

• Remaining samples (n=~3,100) reclustered

• 4,048 samples re-called using clusters from best performing samples

• Final call rate >97.7%. Only 85 samples having call rates <92%.

• Mendelian inconsistencies and gender mismatches still being

resolved.

Minor Allele Frequencies of Selected SNPsLoci

Risk Allele Frequency (RAF)Caucasians African Americans

SNP* Gene* Cases* Controls (Hapmap CEU) Cases Controls

rs5743289 NOD2 0.024 0.226 0.056 0.033

rs12994997 ATG16L1 0.523 0.575 0.352 0.311

rs11209026 IL23R 0.933 0.959 0.989 0.986

rs12942547 STAT3 0.580 0.545 0.597 0.582

rs516246 FUT2 0.483 0.531 0.517 0.495

rs4246905 TNFSF15 0.709 0.676 0.928 0.932

rs17293632 SMAD3 0.235 0.230 0.077 0.068

rs3024505 IL10 0.160 0.181 0.065 0.048

rs10781499 CARD9 0.412 0.487 0.319 0.284

rs4728142 IRF5 0.444 0.398 0.288 0.287

rs6871626 IL12B 0.337 0.367 0.232 0.191

rs10758669 JAK2 0.349 0.366 0.23 0.206

rs3197999 MST1 0.296 0.259 0.25 0.241

*Jostins L et al. Nature. 2012 Nov 1;491(7422):119-24

Exome Sequencing –A pilot project

Sample size: 27 CD patients

20 samples with severe perianal disease phenotype

7 samples with of early onset disease

17 novel functional variants in 16 genes could be implicated in neutrophil dysfunction (validation in progress)

• Through collaborations, we have assembled a well powered, well phenotyped a understudied US population (AA, both adults and children) for genetic studies

• Immunochip studies, GWAS and sequencing (exome & whole genome) studies in AA are underway in both adult and children.

• Admixture analysis is a powerful way to narrow down the causatice loci when admixed population like AA is studied.

• We will be able to these results in risk stratification and prognostic utility in minority population directly rather than extrapolating the Caucasian found results.

Conclusions & Future directions

Acknowledgements to our partnersNIH/NIDDK Genetic consortium