The genetics of autoimmunity document discusses several key points: 1) It examines genetic overlaps between various autoimmune diseases using data from Denmark, finding significant overlaps between diseases like type 1 diabetes, celiac disease, and multiple sclerosis. 2) It details a cross-disease genome-wide association study involving over 10,000 cases across 7 autoimmune diseases to systematically test for genetic overlaps. 3) The study finds several loci significantly associated across multiple diseases, suggesting shared genetic risk factors. It develops methods to analyze association patterns across diseases and examine relatedness between disease groups. 4) The document concludes that defining clear functional clusters across the genome could help elucidate shared disease mechanisms and pathways of

1. The genetics of autoimmunity
Chris Cotsapas
MGH/Broad
chrisc@chgr.mgh.harvard.edu

2. March 2008

3. See also Zhernakova,
van Diemen and
Wijmenga NRG 2009.

4. Co-occurrence in Denmark
T1D Celiac MS CD Ps RA SLE
T1D -- 108 147 217 442 616 46
Celiac 4.2 -- 6 101 13 21 3
MS 1.2 1.0 -- 36 39 43 14
CD 1.7 16.7 1.2 -- 95 148 13
Ps 3.2 2.3 1.4 3.3 -- 372 19
RA 1.9 1.7 0.8 2.8 6.4 -- 226
SLE 2.2 2.7 2.5 2.5 4.1 24.0 --
Lower tri is pairwise OR
Upper tri is overlapping cases
condensed from
Eaton et al J Autoimm 2007

5. Systematically test genetic
overlaps
• Independent discovery implies false negatives
• Compile multiple GWAS
– Cross-phenotype “meta” analysis

6. Participating studies
Disease Study Cases Controls
Celiac Disease 778 3000 †
Crohn's Disease IBDGC 3230 4829 ††
Multiple Sclerosis IMSGC 1851 4900 ††
Psoriasis CASP 1359 1400
Rheumatoid Arthritis EIRA 660 658
NARAC 873 1196
WTCCC 1860 10606 ††
3398 12460
Type I Diabetes WTCCC 2800 3000 ††
FOCiS NoC † includes 1958 Birth Cohort
†† includes 3K WTCCC

7. Locus selection
• Replicated GWAS hit (03/2008)
– Combined p < 5 x 10-7
• Not in the MHC!
– Extensive LD structure in region
• Sufficient data for 43 of 48 loci
– Others not captured across platforms

8. How to analyze across diseases?
Celiac Crohn’s MS Psoriasis RA T1D
0.5 1 x 10-20 0.46 0.98 0.7 0.35
0.04 0.0009 0.9 0.006 0.03 0.02
0.76 0.04 0.54 0.38 0.04 0.02
with Ben Voight

9. Binning p-values
P value range Bin Probability
1 – 0.05 0 0.95
0.05 – 0.001 1 0.049
0.001 – 1x10-6 2 9 x 10-4
< 1x10-6 3 9 x 10-7
with Ben Voight

10. How to analyze across diseases?
Celiac Crohn’s MS Psoriasis RA T1D
0.5 1 x 10-20 0.46 0.98 0.7 0.35
0.04 0.0009 0.9 0.006 0.03 0.02
0.76 0.04 0.54 0.38 0.04 0.02
with Ben Voight

11. How to analyze across diseases?
Celiac Crohn’s MS Psoriasis RA T1D
0 3 0 0 0 0
1 3 0 1 1 1
0 1 0 0 1 1
with Ben Voight

12. CPMA
SNP 0 1 2 3 statistic
rs2076756 4 1 0 0 1.44
rs1464510 4 1 0 0 1.44
rs6441961 4 1 0 0 1.44
rs2188962 4 1 0 0 1.44
rs4613763 4 1 0 0 1.44
rs3761847 4 1 0 0 1.44
rs12251307 4 1 0 0 1.44
rs4963128 5 1 0 0 1.14
rs9888739 5 1 0 0 1.14
rs844644 6 0 0 0 0.62
rs30187 6 0 0 0 0.62
rs11264798 6 0 0 0 0.62
rs1990760 5 0 0 0 0.51
rs7574865 5 0 0 0 0.51
rs2241880 5 0 0 0 0.51
rs17810546 5 0 0 0 0.51
rs3924462 5 0 0 0 0.51
rs11747270 5 0 0 0 0.51
rs1445898 5 0 0 0 0.51
rs4263839 5 0 0 0 0.51
rs2024092 5 0 0 0 0.51

13. CPMA
SNP 0 1 2 3 statistic
rs11209032 3 1 0 2 49.46
rs6679677 3 0 1 1 32.25
rs17388568 2 1 2 0 23.32
rs17696736 1 3 1 0 22.51
rs2542151 3 0 2 0 21.21 PCPMA < 0.01
rs12722489 2 3 0 0 11.57
rs6822844 2 3 0 0 11.57 expect 0 by chance
rs2816316 3 1 1 0 10.65
rs12708716 3 1 1 0 10.65
rs3087243 3 1 1 0 10.65
rs10045431 3 1 1 0 10.65
rs6920220 3 1 1 0 10.65
rs11465804 4 0 1 0 9.22
rs917997 4 0 1 0 9.22
rs10499194 4 0 1 0 9.22
rs13277113 5 0 1 0 8.92
rs11190140 3 2 0 0 5.64
rs10995271 3 2 0 0 5.64
rs2292239 3 2 0 0 5.64
rs6897932 3 2 0 0 5.64
rs1738074 3 2 0 0 5.64

14. Patterns in association across
diseases
Celiac Crohn’s MS Psoriasis RA T1D
0 3 0 0 0 0
1 3 0 1 1 1
0 1 0 0 1 1

15. Disease categories
P < 1e-6
1e-6 < P < 1e-3
1e-3 < P < 0.05
0.05 < P < 0.95
1e-3 < P < 0.05
1e-6 < P < 1e-3

16. P < 1e-6
1e-6 < P < 1e-3
1e-3 < P < 0.05
0.05 < P < 0.95
1e-3 < P < 0.05
1e-6 < P < 1e-3

17. Celi CD MS Psor RA T1D
0.69 1.68 2.03 1.43 1.46 6.50
2.17 2.54 1.01 1.43 5.10 5.00
3.36 2.01 1.15 0.91 1.82 0.97
0.62 6.21 2.68 2.50 1.61 1.11

18. • Are these groups
meaningful?
– molecular processes
– “mechanisms”
• If so, might expect
proteins in loci to
interact
– snp-snp distances should
correlate
– ppi paths should be
short

19. Assessing locus protein connection
L1
0.2
0.75
1.0
0.3 0.78
0.68
L2
0.4 0.1
0.4 0.98
with Kasper Lage
and Lizzy Rossin

20. SNP-SNP distance correlation
DZ DPPI
1 1
0.3 1 0.4 1
0.6 0.7 1 0.4 0.8 1
with Kasper Lage,
Lizzy Rossin and
Anthony Philippakis

21. with Kasper Lage
and Lizzy Rossin

22. Celi CD MS Psor RA T1D
0.69 1.68 2.03 1.43 1.46 6.50
2.17 2.54 1.01 1.43 5.10 5.00
3.36 2.01 1.15 0.91 1.82 0.97
0.62 6.21 2.68 2.50 1.61 1.11

23. Genome-wide data
• Define functional clusters
– Complete
– Accurate
– Interpretable
• Define sets of diseases with shared liability
– Set-specific mechanisms
– Leverage power for new insight
– Mechanistic hypotheses

24. Joint analysis: Crohn’s and MS
• Epidemiologically linked
• Minuk & Lewkonia 86, Sadovnick et al 89
• GWAS meta-analysis data:
– Barrett et al 2008
– De Jager et al 2009
• Criteria
– Joint p < 1 x 10-5
– Per-disease p < 0.01
– Consistent effects

25. CHR BP SNP JointP clumpSNPs CD.P MS.P Direction Genes (100kb window)
1 67437141 rs10889677 3.20E-19 15 1.33E-21 0.00177 ++ IL23R
1 197613252 rs7522462 7.73E-09 24 8.31E-06 0.000208 -- C1ORF106
2 61129193 rs10188217 2.32E-06 16 2.66E-05 0.0132 -- PUS10
2 230983017 rs6710297 3.03E-07 7 0.000124 0.000663 -- SP140
4 42949449 rs1436475 9.65E-06 24 0.0206 8.10E-05 -- 4p13
4 47416600 rs6447568 2.12E-06 14 0.000392 0.00157 ++ ATP10D/KIAA1487
5 40437266 rs17234657 5.75E-17 2 2.87E-19 0.00418 -- PTGER4
5 40473705 rs9292777 3.85E-23 24 3.42E-19 4.25E-07 ++ PTGER4
5 40534334 rs1505992 4.18E-10 27 4.96E-11 0.0236 -- PTGER4
5 158615778 rs254837 1.69E-07 3 0.00123 3.09E-05 ++ UBLCP1/RNF145/IL12B
5 159062555 rs16750 5.15E-06 9 2.46E-05 0.0258 ++ 5q33
9 547340 rs10975130 4.72E-06 20 0.0558 5.11E-06 -- KANK1
9 4971602 rs10758669 1.88E-08 32 3.94E-06 0.000846 -- JAK2
10 6142018 rs12722489 1.11E-06 6 0.00922 1.82E-05 -- IL2RA
10 101314426 rs1332102 1.20E-08 18 3.04E-08 0.0117 -- NKX2.3
11 60570507 rs12276967 1.62E-06 10 0.0134 1.64E-05 ++ CD6 *
16 11260805 rs243327 9.27E-06 17 0.00203 0.00145 ++ SOCS2/C16ORF75/TNP2/PRM2/PRM1/PRM3
16 11311394 rs12928822 6.16E-06 17 0.000362 0.0047 -- SOCS2/C16ORF75/TNP2/PRM2/PRM1/PRM3
16 47211576 rs1872656 3.23E-07 1 0.000352 0.00026 ++ N4BP1
16 84549206 rs11642873 8.44E-08 8 1.11E-05 0.00146 ++ IRF8 *
17 9529440 rs9906593 4.49E-06 7 0.0039 0.000316 -- WDR16/USP43
17 35294289 rs2872507 6.70E-07 15 1.06E-05 0.0087 ++ IKZF3/ZPBP2/GSDMB/ORMDL3
20 44188518 rs3746821 1.81E-06 9 0.00132 4.00E-04 ++ CD40

26. CHR BP SNP JointP clumpSNPs CD.P MS.P Direction Genes (100kb window)
1 67437141 rs10889677 3.20E-19 15 1.33E-21 0.00177 ++ IL23R
1 197613252 rs7522462 7.73E-09 24 8.31E-06 0.000208 -- C1ORF106
2 61129193 rs10188217 2.32E-06 16 2.66E-05 0.0132 -- PUS10
2 230983017 rs6710297 3.03E-07 7 0.000124 0.000663 -- SP140
4 42949449 rs1436475 9.65E-06 24 0.0206 8.10E-05 -- 4p13
4 47416600 rs6447568 2.12E-06 14 0.000392 0.00157 ++ ATP10D/KIAA1487
5 40437266 rs17234657 5.75E-17 2 2.87E-19 0.00418 -- PTGER4
5 40473705 rs9292777 3.85E-23 24 3.42E-19 4.25E-07 ++ PTGER4
5 40534334 rs1505992 4.18E-10 27 4.96E-11 0.0236 -- PTGER4
5 158615778 rs254837 1.69E-07 3 0.00123 3.09E-05 ++ UBLCP1/RNF145/IL12B
5 159062555 rs16750 5.15E-06 9 2.46E-05 0.0258 ++ 5q33
9 547340 rs10975130 4.72E-06 20 0.0558 5.11E-06 -- KANK1
9 4971602 rs10758669 1.88E-08 32 3.94E-06 0.000846 -- JAK2
10 6142018 rs12722489 1.11E-06 6 0.00922 1.82E-05 -- IL2RA
10 101314426 rs1332102 1.20E-08 18 3.04E-08 0.0117 -- NKX2.3
11 60570507 rs12276967 1.62E-06 10 0.0134 1.64E-05 ++ CD6 *
16 11260805 rs243327 9.27E-06 17 0.00203 0.00145 ++ SOCS2/C16ORF75/TNP2/PRM2/PRM1/PRM3
16 11311394 rs12928822 6.16E-06 17 0.000362 0.0047 -- SOCS2/C16ORF75/TNP2/PRM2/PRM1/PRM3
16 47211576 rs1872656 3.23E-07 1 0.000352 0.00026 ++ N4BP1
16 84549206 rs11642873 8.44E-08 8 1.11E-05 0.00146 ++ IRF8 *
17 9529440 rs9906593 4.49E-06 7 0.0039 0.000316 -- WDR16/USP43
17 35294289 rs2872507 6.70E-07 15 1.06E-05 0.0087 ++ IKZF3/ZPBP2/GSDMB/ORMDL3
20 44188518 rs3746821 1.81E-06 9 0.00132 4.00E-04 ++ CD40

27. Acknowledgements
Mark Daly Goncalo Abecasis
Ben Voight Jeff Barrett
Elizabeth Rossin Judy Cho
Kasper Lage JT Elder
Ben Neale Michel Georges
Anthony Philippakis Peter Gregersen
David van Heel
David Hafler Lars Klareskog
Steve Rich Leonid Padyukov
Robert Plenge
Cristin Aubin Soumya Raychaudhuri
Phil de Jager John Rioux
John Todd
Sarah Krause Cisca Wijmenga

28. TH17 cell involvement in MS?
IL12
B
NKX2.3
IL12B
IL23R JAK2
STAT3

29. Analysis!
Celiac Crohn’s MS Psoriasis RA T1D CPMA
0.5 1e-20 0.46 0.98 0.7 0.35 No
0.05 1e-3 0.9 0.006 0.05 0.02 Yes
0.76 0.05 0.54 0.38 0.04 0.06 Yes

30. 12/19 loci
P ~ 1e-3 connected
P ~ 4.3e-3
P ~ 0.057
P ~ 7.8e-4
with Kasper Lage
and Lizzy Rossin