Genetic Testing and the Prevention of Type 1 Diabetes

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Genetic Testing and the Prevention of Type 1
Diabetes

• Janice S. Dorman, Ph.D.
• September 4, 2001

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Type 1 Diabetes

• One of most frequent chronic diseases of children
  
• - Prevalence 2 / 1000 in Allegheny County, PA
• Epidemiology of type 1 diabetes has been studied
  at the University of Pittsburgh since 1979
• - Dr. Allan Drash and Dr. Lewis Kuller

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Type 1 Diabetes IncidenceAllegheny County, PA
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Type 1 Diabetes Incidence Allegheny County, PA
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Type 1 Diabetes Incidence Allegheny County, PA
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FIN
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Type 1 Diabetes Incidence Worldwide
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Specific Environmental Risk Factors

• Case-control studies - conflicting
• Possible risk factors
• - Infant diet or lack of breast feeding
• - Childhood diet
• - Viruses (exposure as early as in utero)
• - Hormones
• - Stress
• May act as initiators or precipitators

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Evidence for Genetic Risk Factors

• Increased risk for 1st degree relatives of
  affected individuals
• Concordance in MZ twins 20 - 50
• Recent genome wide screens have revealed 15
  possible susceptibility genes
• Associations with HLA class II alleles in all
  populations

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Genome Screens for Type 1 Diabetes

• IDDM1 6p21.3
• IDDM2 11p15.5
• IDDM3 15q26
• IDDM4 11q13.3
• IDDM5 6q15
• IDDM6 18q12-q21
• IDDM7 2q31-33
• IDDM8 6q25-27

• IDDM9 3q21-25
• IDDM10 10p11-q11
• IDDM11 14q24-q31
• IDDM12 2q33
• IDDM13 2q34
• IDDM14 ND
• IDDM15 6q21

Candidate Gene Possible Candidate No
Candidate Gene
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Interpreting Linkage Analysis for Type 1Diabetes

• Need to control for effect of HLA
• Some genes confer susceptibility in absence of
  high risk HLA haplotypes
• Need model- free statistical methods
• Account for gender, parent-of-origin effects and
  environmental risk factors
• May not be appropriate phenotype

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Genome Screens for Type 1 Diabetes

• Chromosome 6
• IDDM8 6q25-27
• IDDM15 6q21
• Chromosome 2
• IDDM7 2q31-33 HOX8, IL-1 family IDDM12 2q33
  CTLA4, CD28 IDDM13 2q34 IGFBP2,
  IGFBP5

Candidate Gene Possible Candidate No
Candidate Gene
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Genome Screens for Autoimmune Diseases

• Candidate Genes - Type 1 Diabetes
• IDDM1 6p21.3 DR-DQ, 2nd loci - TNF?
• IDDM2 11p15.5 INS-VNTR
• IDDM12 2q33 CTLA4, CD28
• Candidate Genes - Other Disorders
• IDDM1 ATD, CD, RA, MS, SLE
• IDDM2 SLE, ankylosing spondylitis
• IDDM12 ATD

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WHO DiaMond Molecular Epidemiology Study

• Have evaluated HLA DQ
• Best single genetic marker
• Evaluate other candidate genes
• IDDM1 HLA DR, DP
• IDDM2 INS-VNTR
• IDDM12 CTLA4
• Others VDR, HLA class I

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WHO Multinational Project for Childhood Diabetes
(DiaMond)

• What is Causing the Tremendous Geographic
  Variation in Incidence of Type 1 Diabetes?
• Monitored Incidence Worldwide
• 1990 - 2000

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WHO Collaborating Center for Diabetes Registries,
Research and Training

• Ron LaPorte, Ph.D. Disease Monitoring
  Telecommunications
• Jan Dorman,Ph.D. Molecular Epidemiology
• University of Pittsburgh

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WHO DiaMond Molecular Epidemiology Study

• Hypothesis
• Geographic differences in type 1 diabetes
  incidence reflect population variation in the
  frequencies of disease susceptibility genes
• 20 countries participating
• Focus on 2, 1, or 0 high risk HLA-DQ haplotypes
  (SS, SP, PP)

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Relative Increase In Risk

• Population SS SP PP
• Caucasian 15.9 4.0 1.0
• Af Americans 44.8 7.3 1.0
• Asian 10.7 3.6 1.0
• p lt 0.05, test for trend
• Allegheny Co, PA and Jefferson Co, AL
• Hokkaido, Japan and Seoul, Korea

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Cumulative Risk Through Age 30 Years

• Population SS SP PP
• Caucasian 2.6 0.7 0.2
• Af Americans 3.1 0.5 0.1
• Asian 0.2 0.1 0.02
• Allegheny Co, PA and Jefferson Co, AL
• Hokkaido, Japan and Seoul, Korea

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Population Attributable Fraction

• Population SS SS or SP
• Caucasian 36.2 66.6
• Af Americans 43.5 74.9
• Asian 18.8 53.3
• Allegheny Co, PA and Jefferson Co, AL
• Hokkaido, Japan and Seoul, Korea

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What do these data tell us?

• Increased risk for individuals with SS and SP
  genotypes, relative to PP, with a significant
  dose response
• Cumulative risk for SS individuals in
  high-moderate incidence countries approaches
  rates for first degree relatives 3 - 6

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What do these data tell us?

• Contribution of the highest risk HLA-DQ genotypes
  to type 1 diabetes incidence varied from 19 -
  43 across populations
• More than 50 of the incidence of type 1 diabetes
  is NOT explained by the highest risk HLA-DQ
  genotypes

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Gene - Environment Interactions
Finland

• Exposure increased risk by 1/100,000 / year
  among susceptibles
• Overall population risk would increase by 0.8

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Gene - Environment Interactions
China

• Exposure increased risk by 1/100,000 / year
  among susceptibles
• Overall population risk would increase by 10

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Molecular Epidemiology of Type 1 Diabetes in China

• What is contributing to the low overall incidence
  and large variation in risk within China?
• - Etiological heterogeneity
• - Susceptibility genes
• - Environmental risk factors
• Project based on DiaMond registry network
• Model study for molecular epidemiology

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0
1.8
Rate (per 100,000)
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Molecular Epidemiology of Type 1 Diabetes in China

• Data collection completed in 1999 - Dr. Yang
  Ze
• 296 cases, 528 controls 18 centers
• Molecular analyses - Beijing
• - HLA DRB1, DQB1 typing
• Serological analyses - Pittsburgh
• - GAD, IA-2, TPOAb, TGAb, C-pep
• Environmental data - Pittsburgh
• - Nutrition, infections, pollution
• Dissertation for Dr. Elsa Strotmeyer

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Jan Alice Lew Yang Ze