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u Autoimmune diseases afflict some 50 million people in the US.
u Systemic autoimmunity (SLE, RA)
uOrgan-specific autoimmunity• Single organ (IDDM, Thyroid disease)• Multiple organs (APS)
Inherited and Acquired Risk for Autoimmunity
Inherited and Acquired Risk for Autoimmunity
uMonogenic disorders– APS1 (APECED)
– Genetically homogeneous, Phenotypically homogenous
u Acquired disease– Chemical- or virus -induced
u Multifactorial diseases• SLE• Multiple sclerosis, etc.• Type 1 diabetes
• Genetically heterogeneous, phenotypically homogeneous
Autoimmune PolyglandularSyndromes (APS)
uAPS1 (APECED): > 2 of 3 disorders• Hypoparathyroidism (HPT)• Addison’s disease (AD)• Mucocutaneous candidiasis (MC)
uAPS2: AD plus IDDM or autoimmune thyroid diseases (ATD)
uAPS3: ATD and others but no AD
Component Diseases and their Frequencies in Autoimmune Polyglandular Syndromes
Component Diseases
Endocrine components:Hypoparathyroidism
Addison Disease
Hypothyroidism
Hyperthyroidism
IDDM
Ovarian failure
Testicular failure
Pernicious Anemia
Hypopituitarism
APS1 APS2 APS3
80%
70% (early)
5%
0%
2-5%
60%
14%
15% (early)
+-
0%
100% (late)
70%
++
52%
4%
2%
1% (late)
+
0%
0%
70%
+-
+-
0%
0%
++
--
Component Diseases and their Frequencies in Autoimmune Polyglandular Syndromes
Component Diseases APS1 APS2 APS3
Non-endocrine components:Mucocutaneous Candidiasis
Alopecia
Vitiligo
Chronic active hepatitis
Keratopathy
Squamous cell carcinoma, Septicemia
Intestinal Malabsorption
Enamel hypoplasia
90%
26%
10%
11%
35%
++
18%
77%
0%
1%
5%
0%
0%
+
0%
0%
0%
+-
>10%
0%
0%
--
0%
0%
Distribution of Numbers of Disease Components Among APS1 Patients
0
5
10
15
20
25
30
% o
f C
ases
1 2 3 4 5 6 7 8
No. of Disease Components
APS 1
uRare: <1/100,000
uRecessively inherited
uSingle gene on chromosome 21q
Hypothetical structure of AIRE
Gel Shift Assay with AIRE Consensus sequence
ChIP mop ChIP
Fig. 3: ChIP microarray analysis with mouse thymus. Green spots indicate higher intensities for the ChIP-enriched probes than the unenriched probes and most likely contain sequence sites bound by the Aire protein. Yellow (equal intensities for both probes) or red (lower intensities for the ChIP-enriched probe) represent non-specific immunoprecipitated DNA (noise).
Search for target genes regulated by AIRE- Chromatin Immunoprecipitation Microarray
Fig3. Expression differences measured by semiquantitative RT-PCR of 11 genes from Aireknock-out mice, B6 mice was used as control.cDNAs were normalized to B-actin. Experiment has been done in 2 independently isolated MECsamples from both Aire knock-out and B6 mice.
Mechanism of Disease
Regulation of autoantigen expression in the thymus. Deficiencies in expression of peripheral autoantigens in thymus results in defective elimination of autoreactive T cells.
Regulation of key cytokines and growth factors involved in thymocyte development.
AIRE gene
1 2 3 4 5 6 7 8 9 10 11 12 13 14
AIRE protein
1 545L L L LPHD1 PHD2PRR
Mutations
R15L
L28P T90C
K83E
IVS3+1T/C
R203X
R257X13bpdel
ins CCTG
1249 del C1264 del C
1313 del C
1422 ins AC
X546C
1291 ins A
R139X318-353del
Q173X
IVS9-1G/A
1284 ins A
1320 del C1391 del C
The Autoimmune Regulator (AIRE) is Mutated in APS1 Patients
Population Frequencies of Major Mutations
82%
13%0%
5%
73%
27%
0%
0%
56%28%
16%
0%
95%
0%5%0%
0%
14%
64%
22% Mutations:
1) R257X
2) 13bpdel
3) R139X
4) Others
Finland Italy Sardinia
UK US
Type 1 Diabetes (T1D or IDDM)Type 1 Diabetes (T1D or IDDM)
u Due to destruction of pancreatic beta cells by one’s own immune system
♦ Autoantibodies: IAA, ICA, GAD & IA2♦ Autoreactive T cells
u Affects 0.4% of the population (1 million Americans)
u Age of onset for most patients: before 17 yearsuMultifactorial disease
♦ ~50% concordance in MZ twins♦ Multiple genetic factors♦ Environmental triggers
Type 1 DiabetesType 1 Diabetes
Environment Immune Response
Genetics
Natural History of Type 1 DiabetesNatural History of Type 1 Diabetes
Genetic Predisposition
Prediabetes/Autoimmunity(Autoantibodies,Insulitis)
Clinical Disease
- virus- diet- toxins
- virus- diet - toxins
Initiators Promoters
IDDM Susceptibility Intervals in Humans (2004)IDDM Susceptibility Intervals in Humans (2004)
Loci Region Genes/Status
IDDM 1IDDM 2IDDM 3IDDM 4IDDM 5IDDM 6IDDM 7IDDM 8IDDM 9IDDM 10IDDM 11IDDM 12IDDM 13IDDM 15D14S70-D14S276D16S515-D16S520D19S247-D19S226
D19S225D1S1644-AGT
6p2111p1515q2611q136q2518q2q336q273q10p13-q1114q24-q312q332q336q2114q12-q2116q22-q2419p1319q131q
HLA-DR, DQ and othersInsulin??
??????CTLA4???
???
IDDM18 - IL12p40
Controls NFkB
?
HLA Genotypes % in % in IDDM Absolute RiskDR-DQB1/DR-DQB1 controls (Sensitivity) (Specificity)
03-0201/04-0302 (DR3/4) 1.8 35.0 1/15
04-0302/04-0302 (DR4/4) 0.7 10.0 1/20
03-0201/03-0201 (DR3/3) 1.5 9.0 1/40
04-0501/04-0301 (DR1/4) 0.6 2.0 1/60
15-0602/ 50.7 20.0 1/15,000
Predictability for IDDM Risk by HLAPredictability for IDDM Risk by HLA
Family History Increases Risk for T1DFamily History Increases Risk for T1D
1st Degree Relative
1/4-5
1/8
1/10
1/15
1/125
1/15,000
GeneralPopulation
1/15
1/30
1/40
1/60
1/600
1/15,000
DR/DQ
DR 3/4, DQ 0201/0302
DR 4/4, DQ 0300/0302
DR 3/3, DQ 0201/0201
DR 4/X, DQ 0302/X
X/X, 3/X
DR 0403 or DQ 0602
Islet Cell Autoantibodies increase Islet Cell Autoantibodies increase specificity of the screeningspecificity of the screening
uMeasure 4 autoantibodies ♦ GADA: Glutamic acid decarboxylase autoantibody
♦ IA2A: Insulinoma-associated antigen 2 autoantibody
♦ IAA: Insulin autoantibody
♦ ICA Islet cell autoantibody
Timing and Sequence of Ab AppearanceTiming and Sequence of Ab Appearance
0
1
2
3
4
5
18m 20m 22m 24m 30m 33m 39mIDD
Age (months)
Ab
Tite
r
GAD IA-2A Cut off
1
10
100
1000
18m 20m 22m 24m 30m 33m 39mIDD
Age (months)
Ab
Tite
r
ICA ICA Cutoff IAA IAA Cutoff
0
1
2
3
4
5
12m 15m 18m 21m 24m 27m 33m 36mIDD
39m 42m
Age (months)
Ab
Tite
r
GAD IA-2A Cutoff
1
10
100
1000
12m 15m 18m 21m 24m 27m 33m 36mIDD
39m 42m
Age (months)
Ab
Tite
r
ICA ICA Cutoff IAA IAA cutoff
Specificity and Sensitivity of AbScreening in Relatives
00.10.20.30.40.50.60.70.80.9
0 0.01 0.02 0.03 0.04
1-Specificity
Sens
itivi
tyiY
ICA&IA2ß
GAD
ICA&GAD ICA&IAA
IA2ß
GAD or IAA GAD or ICA
IAA
GAD or IA2ß
ICAGAD or IA2
ICA&IA2
???
MicroarrayMicroarray--based prediction markersbased prediction markers
AbN T1D AbPAbN T1D AbP
118 genes
AbP/IDD vs AnN
18 genes
AbP vs IDD
MultiMulti--gene Modelsgene Models
Model 11276, 65 clones
Canonical Variate 2
Can
onic
al V
aria
te 1
Ab-Ab+Idd
Normal Kernel Model
1 of 5 models
4-9% error
Model 16562, 35 Clones
Canonical Variate 2
Can
onic
al V
aria
te 1
Ab-Idd
Discovery of two subsets of AbP SubjectsDiscovery of two subsets of AbP Subjects
Model 16562, 35 Clones
Canonical Variate 2
Can
on
ical
Var
iate
1
Ab-IddAb+
Progression to Diabetes among AbP SubjectsProgression to Diabetes among AbP Subjects
0
0.25
0.5
0.75
1
0 1 2 3 4
Time of Follow-Up (years)
Pro
bab
ility
of S
urv
ival
AbN- like
T1D- like
n=6
n=13
TEDDY Centers(preceding study, year started)
• Colorado (DAISY, 1993) • Finland (DIPP, 1994)• Georgia/Florida (PANDA, 1997)• Germany (BABY-DIAB, 1989)• Sweden (DiPiS, 2000)• Washington (DEW-IT, 2000)• Data Coordinating Center (Tampa, FL)
The Environmental Determinants of Diabetes in the Young (TEDDY)
TEDDY Screening and Enrollment
Pregnant Women
Newborns
Screening for HLA-DR,DQ genotypes
Low-RiskExcluded from Study
95% of general population70% of first-degree relatives
High/Moderate RiskFollow up
5% of general population30% of first-degree relatives
Europe:FinlandSwedenGermany
N. America:ColoradoGeorgia/FloridaWashington
Sibling/offspring cohort
6 centers
General population cohort
6 centers
Screened = 216,000 = 4,800
Eligible (high risk) = 11,880 (5.5%) = 1,440 (30%)
Enrolled = 5,940 (50%) = 1,152 (80%)
Autoimmunity cases= 238-500 = 152-300 by age 15
T1DM cases = 238 (4%) = 152 (13.3%) by age 15
TEDDY Proposed Study Population
Major Goals of TEDDY
Identify environmental triggers for T1DInfectious agentsDietary factorsPsycho-social factors
Understand gene/environment interactions
Refine screening strategies
Summary
Individuals predisposed to monogenic autoimmune diseases are readily detectable by newborn screening.
Most common autoimmune diseases are multifactorial.
Multifactorial diseases can be predicted by a combination of genetic and other risk factors.
Screening for autoimmunity may soon become an important issue for PHL.
AcknowledgementsAcknowledgementsMouse microarray
Sarah Eckenrode, Ph.DQingguo Ruan
Ping Yang
Weipeng ZhengQuanZhen Li, Ph.DHuman microarray
HongShan Zhao, Ph.D
Christin Collins
PANDAAndy Muir, M.D.Diane HopkinsAna CaroDesmond Schatz, MDMark Atkinson, PhD
University of Colorado, Denver
Marian Rewers, MD
George Eisenbarth, MD, Ph.D
& DAISY team
Proteomics
Sharad Purohit, Ph.D,
Dan Eisenman
BioinformaticsRichard McIndoe, Ph.DYan Zhang, Ph.D Yihua Huang, Ph.DJohn Hopkins
BiostatisticsRobert Podosky, Ph.DMark Yang, Ph.D, Prof.James Yang, Ph.D
uGet Get TEDDY slides
Day 3 Thymectomized Mice
uDevelop organ-specific autoimmunity• Prostatitis• Orchitis• Epididymovasitis• Thyroiditis• Gastritis• Oophoritis
uDeficiency in CD4+ CD5high regulatory T-cells
Induction of Autoimmune Diseases in Mice by Eliminating CD4+ and CD25+ (IL-2Rα+) T-cells
uOrgan-specific autoimmune diseasesuGraft-versus-host disease (GVHD)-like
wasting disease
• Gastritis
• Oophoritis
• Thyroiditis
• Insulitis
• Adrenalitis
• Glomerulonephritidis
• Sialoadenitis
• Arthritis
Mater(Maternal effect gene)
B6 KO
B-actin 1
B-actin 2
2nd PCR
B-actin 3
B-actin 4
B-actin 5
B6 KO
B-actin
1
2Mgat5 (32X)
No difference found: ATP4a, ATP4b
No amplification in TEC:After nest PCR: EAPA1, EAPA2
1st PCR: BMP1, BMP5, BMP8a, INF_gamma, GAD65
BMP8bBMP10
B-actin
ICA69
Rbp3 (nest PCR)
Hypothetical KRAB box containing protein
B-actin
KRAB
Ag H Ki Li LN Lu Ov Pa Mu Sp Te Th BMDC Pr
B-actin
HPRT
4F9R
B6 Aire-/-
Aire expression in Bone-Marrow DC
N Thymus1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8
S1 S2 S3 T1 T2 T3 T4 T5 C1 C2 P MS1 S2 S3 T1 T2 T3 T4 T5 C1 C2 P M
Bone morphogenetic protein
S1 S2 T1 T2 T3 T4 T5 C1 C2 P M
Mannoside acetylglucosaminyltransferase V (Mgat5)
Fig. 4: PCR confirmation of Aire/DNA complexes from ChIP. ChIP-enriched DNA was amplified using primers specific for the flanking region of the Aire binding site. Two genes are shown here as examples. S1-S3: NOD spleen pools. T1-T5: Thymus pools 1-5. C1 & C2: Mock ChIP control. P: positive control using regular mouse genomic DNA. M: marker.
0
2040
60
80
100
120
140160
1 2
Tgn + control
Tgn + AIRE
0
2040
60
80
100
120
140160
1 2
Fabp2 + control
Fabp2 + AIRE
Thyroglobulin Fatty acid binding protein 2
Fig. 6: Luciferase co-transfection assay for promoter activity. Data from two replicates were shown for each promoter.
AIRE binds to the promoters with specific sequence motifs
AIRE Contains Protein Domains of Transcription Factors
u4 LXLL motifs: binds nuclear receptorsu1 SAND domain: mediates DNA
interaction of nuclear proteinsu2 PHD (CYS4-His-CYS3) zinc-finger
domains found in transcription factorsu1 proline rich region
+/+ -/-
B-actin
Bmp 9
Fig. 5: PCR analysis of expression of the bone morphorgentic protein 9 (Bmp 9) in whole thymus tissue from Aire(+/+) and knockout Aire(-/-) mice. mRNA was reversed transcribed into cDNA. Serial dilutions (2 fold) of the RT products were used as template for RT-PCR for β actin (26 cycles) and Bmp 9 (30 cycles).
1 1/2 1/4 1/8 1/16 1 1/2 1/4 1/8 1/16 Dilution
Expression difference in KO mice
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