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Cytokine Polymorphisms (SNPs)
In Silicosis and Other Chronic Inflammatory
Diseases
Berran Yucesoy, Ph.D.
Toxicology and Molecular Biology Branch
National Institute for Occupational Safety and Health
Morgantown, WV
When the rate of sequence variation at a specific
point in the DNA is more than 1% of a given
population, it is referred to as a polymorphism.
When the incidence of a variant sequence is less
than 1%, it is referred to as a mutation.
About 90% of sequence variants in humans are
differences in single bases of DNA, called single
nucleotide polymorphisms (SNPs)
Classification of SNPs
• Coding region SNPs:
Synonymous: mutation does not change amino acid.
Non-synonymous (replacement): mutation change amino acid
sequence
• Non-coding region SNPs:
5’ and 3’ UTR’s
Introns
Intergenic spacer
SNPs- Application
• Gene discovery and mapping
*physical mapping
*genetic linkage mapping
• Association-based candidate gene testing
• Diagnostics and risk profiling
• Pharmacogenetics
• Homogeneity testing and epidemiological study design
Toxicological Application of SNPs
Family and
Linkage Studies
Candidate Regions
Family Studies
Case - Control cohorts
Association Studies
Positional
Cloning
Candidate Genes
Functional
Studies
Single Gene Disease
Drug-Target Design
Diagnostics
Complex Diseases
Drug-Target Design
Pharmacogenetics
Risk Profiling
SNPs- Advantages
• Very common-high density in genome
• Less mutable than other types of polymorphisms
• Very applicable to serve as a biological biomarker for
genetic susceptibility
• Could be used to enhance gene-mapping
• Could be used in population-based genetic studies
• Advanced technology allows high-throughput genotyping
• A large number of human SNPs are available
• An important addition to human genome project
Genetic Disorders
• Single-gene (monogenic or Mendelian)
• Polygenic (complex or multifactorial)
• Chromosomal
• Mitochondrial
Monogenic Diseases
Cystic Fibrosis
Tay-Sachs
Retinoblastoma
ADD
Hypercholesterolemia
Phenylketoniuria
Huntington
Gaucher Disease
Family Studies
R
R
D
R
D
R
D
R
Polygenic Diseases
Asthma
Mental Disorders (Alzheimer’s)
Cardiovascular
Cancer (ovarian, breast, endometrial)
Periodontal diseases
Autoimmunity
Multifactorial (complex or polygenic)
Diseases
- complex interactions among multiple
genes as well as environmental and
lifestyle factors
-often chronic inflammatory involvement
Modifying Factors and Multifactorial Disease
Occupational
Exposure
Mild - Moderate
SNPs
Severe Disease
Physiological and
Environmental Factors
(e.g., smoking
diet, stress)
Common Disease-Common Variant (CD-CV) Hypothesis
• Alzheimer’s disease - ApoE4 genotype
• Factor V leiden - deep venous thrombosis
• PPAR Pro12Ala – type II diabetes
• CCR5∆32 – HIV
Example of cytokine SNPs found to effect expression
levels and modify disease
Cytokine
• IL-1
• IL-1
• IL-1RA
• IL-4
• IL-6
• IL-10
• IL-13
• TNF-
• TGF-1
Polymorphic locus
• -889, +4845
• -511, +3953
• VNTR, +2018
• -590, +33
• -174, -572
• -627, -1082, -819,-592
• -1055, -1111
• -308, -238
• -509, codon 10, 25
Acute inflammation
• mononuclear cell infiltration
• granulation tissue formation
• fibrosis, angiogenesis and tissue destruction (new vessel
formation)
• regeneration
Chronic inflammation
occurs when acute phase cannot be resolved
Development of pulmonary fibrosis
Injury and inflammation
Epithelial cells
TGF,, IL-1, TNF, PDGF,
IFN, IGF-1
fibroblast
PDGF, TGF,, ET-1, FGF
Inflammatory cells
TGF
Epithelial cells
Fibrosis
Fibroblast, myofibroblast accumulation
and ECM deposition
Dysfunctional parenchyma
Silicosis
-is a chronic fibrosing disease of the lungs
produced by prolonged and extensive
exposure to free crystalline silica.
-presents in two forms , depending on the
duration of exposure
*simple silicosis
*progressive massive fibrosis
Specific Aims
• the role of the IL-1 and TNF SNPs in
silicosis frequency and severity
• Gene-gene interactions
• Gene-gene-environment interactions
Animal Studies
* Increased expression of inflammatory cytokines in
the lung of silicotic rodents (Struhar,1989; Driscoll,1990;
Mohr,1991; Orfila,1998; Davis,1998)
* Resistance of TNF deficient mice to developing
fibrosis from silica (Piguet,1990; Gossart, 1996)
* Protection of TNF receptor knock-out mice against
the fibrogenic effects of silica (Ortiz, 1999)
* Induction of expression of TNF- and its receptors in
C57BL/6J mice exposed to silica (Ohtsuka,1995)
Human Studies
*
Association between the local release of IL-1 and
TNF and pathogenesis of silicosis (Schmidt, 1984;
Savici, 1994)
*
Higher levels of spontaneous TNF and IL-1
secretion by AMs in patients with CWP (Lassalle, 1990)
*
Increased coal mine dust-stimulated release of TNF
from PBM in subjects with pneumoconiosis (Borm,
1988; Schins&Borm,1995; Kim, 1995)
*
Increased TNF release in the lungs of
pneumoconiotic patients (Vanhee, 1995)
*
Up-regulation of cytokines and growth factors in
CWP (Vallyathan, 2000)
Age, smoking status and years of exposure by
disease status
Mean (range; S.D.)
Population
Number of
patient
Age
Years
smoking
Years
exposure
Controls
164
63.2
20.4
21.3
(50-87; 8.0) (0-50; 16.4) (1-58; 13.3)
Moderate
140
66.9
20.5
34.4
(27- 87; 9.2) (0-70; 19.1) (10-52; 10.1)
Severe
185
68.7
17.9
34.2
(39-93; 8.8) (0-60; 18.4) (1-55; 11.3)
Overall
489
66.3
19.5
29.9
(27-93; 9.0) (0-70; 18.0) (1-58; 13.2)
Distribution of genotypes and allele frequencies for IL-1
Disease status
Normal:
1/1 Alleles
Carrier:
1/2 or 2/2
Allele 2
Frequency
Adjusted
OR (CI)**
Controls
113
44
0.16
1.00
Moderate
54
60
0.35
2.54 (1.4-4.5)
Severe
95
65
0.22
2.01 (1.2-3.4)
All Silicotic*
149
125
0.27
2.15 (1.3-3.5)
Controls
125
31
0.10
1.00
Moderate
111
21
0.08
0.47 (0.2-0.9)
Severe
113
42
0.15
0.90 (0.5-1.6)
All Silicotic
224
63
0.12
0.76 (0.4-1.3)
Controls
43
95
0.36
1.00
Moderate
35
75
0.40
0.8 (0.5-1.6)
Severe
55
88
0.36
0.72 (0.4-1.3)
All Silicotic
90
163
0.38
0.75 (0.4-1.2)
IL-1RA(+2018)a
IL-1(+4845)
IL-1(+3953)
*Represents total population studied with silicosis
**odds ratio (95% confidence limits) adjusted for exposure with logistic regression
a Significantly associated with moderate, severe and overall disease
Distribution of Genotypes and Allele
Frequencies for TNF
Disease
status
Normal:
1/1 Alleles
Carrier:
1/2 or 2/2
Allele 2
Frequency
Adjusted OR
(CI)**
Controls
75
79
0.27
1.00
Moderate
40
97
0.37
3.59 (2.0-6.4)
Severe
83
74
0.24
1.61 (0.9-2.8)
All Silicotic*
123
171
0.30
2.25 (1.4-3.6)
Controls
87
73
0.24
1.00
Moderate
91
41
0.16
0.52 (0.3-0.9)
Severe
42
141
0.40
4.00 (2.4-6.8)
All Silicotic
133
182
0.30
1.59 (1.0-2.5)
TNF(-308)a
TNF (-238)a
*Represents total population studied with silicosis
**odds ratio (95% confidence limits) adjusted for exposure with logistic regression
a Significantly associated with moderate, severe and overall disease
IL-1 Normal
IL-1 Variant
Moderate Cases
1.0
A
IL-1RA Normal
IL-1RA Variant
Both Normal
E
Variant in IL-1
Variant in TNF-308
(52)
Variant in Both
0.8
0.6
(136)
(13)
(53)
(37)
(76)
(16)
(24)
(44)
(87)
0.4
(78)
(15)
(49)
(64)
0.2
(28)
(7)
0.0
D
B
(83)
F
(74)
(60)
0.8
Severe Cases
C
(24)
(133)
(36)
0.6
(108)
(21)
(10)
(50)
0.4
(37)
(11)
(71)
(86)
(75)
0.2
(45)
0.0
TNF-238
Normal
TNF-238
Variant
TNF-308
Normal
TNF-308
Variant
Exposure <
30 years
Exposure >
30 years
Gene-gene interactions
Periodontitis
IL-1 - IL-1
Kornman, 1997
Gore, 1998
EOP
IL-1 - IL-1RA
Parkhill, 2000
Silicosis
IL-1RA - TNF
Yucesoy, 2001
Asthma
IL-4RA - IL-13
Howard, 2002
SNP
Disease
Association Reference
IL-1  -889
Juvenile rheumatoid
arthritis
Juvenile chronic arthritis
yes
McDowell, 1995
no
Donn, 1999
IL-1  +3953
Periodontitis
yes
Kornman, 1997, 98
IL-1RA VNTR,
+2018
Ulcerative colitis
Rheumatoid arthritis
yes
yes
Tountas, 1999
Kaijzel, 2002
IL-1  -511
IBD
COPD
yes
no
Nemetz, 1999
Ishii, 2000
IL-4 -590
Asthma
yes
Noguchi, 1998
IL-10 -1082
Alzheimer’s disease
yes
Lio, 2003
IL-6 -174
Alzheimer’s disease
no
yes
Bagli, 2000
Faltraco, 2003
TGF1 -509
Asthma
yes
Pulleyn, 2001
TNF -308
Asthma
Rheumatoid arthritis
yes
yes
Chagani, 1999
Cvetkovic, 2002
TNF  -238
Multiple sclerosis
yes
Huizinga, 1997
IL-16 -295
Crohn’s disease
yes
Glas, 2003
IL-13 -1055
COPD
yes
Pouw Kraan, 2002
Association Studies
Population-based
• Case-control studies
• Cohort studies
If a significant association appears,
• the polymorphism itself is the locus of interest
• the polymorphism is in linkage disequilibrium with the
locus
• confounding factors are present
Family-based
• Parents-affected child trios (TDT)
-looking for unequal transmission of SNP alleles to
affected and non affected siblings
Issues in case-control studies
•
•
•
•
•
•
Population stratification
Genetic heterogeneity
Linkage disequilibrium (LD)
Candidate genes
Random error
Study design problems
Population stratification
Occurs when the cases and controls are
unintentionally drawn from two or more ethnic
groups . Factors responsible could be:
• migration
• geographical distribution
• ecology
• local adaptation
*to use family-based studies such as TDT
*to study multiple case-control populations from
different ethnic groups
Genetic heterogeneity
• Different genetic mechanisms in different
populations
Linkage disequilibrium (LD)
• Association between particular alleles due to
their proximity on the same chromosome
• allows mapping of disease loci in large
populations.
Candidate genes
• Biological plausibility and functional importance
of polymorphisms tested
Random error
• False positive/false negative results
Study design problems
• Small sample size
• Poor control group
• Problem in replication
• Poor defined phenotypes
Expectations
• Prediction of disease
• Disease mechanisms
• Targeted therapy-Pharmacogenetic
(The correlation between an individual’s
genetic make-up and their response to
drug treatment, personalized medicine)
SNP Resources
•
•
•
•
•
•
•
•
http://www.ncbi.nlm.nih.gov/SNP/
http://innateimmunity.net
http://snpper.chip.org
http://www.genome.utah.edu/genesnps/
http://genome.cse.ucsc.edu/
http://pga.lbl.gov/PGA/PGA_inventory.html
http://snp500cancer.nci.nih.gov/home.cfm
http://www.bris.ac.uk/pathandmicro/services
/GAI/cytokine4.htm
Collaborators
• Michael I. Luster, Ph.D
• Val Vallyathan, Ph.D.
• Douglas P. Landsittel, Ph.D.
• Michael L. Kashon, Ph.D.
• Vic Johnson, Ph.D.
• Michael McKinstry
• Kara Fluharty