Transcript Are genetic tests good for population screening?

Genetic mapping studies
- Asthma and allergy
Nature of disease gene projects
Clinical expertise
Genetic analysis
Diagnostic classification Disease modelling
Hopes and aims:
what does one want to find?
• Development of therapies
– New bioactive factors or immediate drug targets
– New pathways or disease mechanisms
– New associations for known pathways
• Development of diagnostics
– Specific assays for disease screening
– Specific diagnostic assays for clinical use
– Informative and useful new assays
How to think of gene effects in
multifactorial diseases?
•
•
•
•
Pedigrees and penetrance
The threshold model of susceptibility
Quantitative gene effects
Diversity of disease-associated variants
How to find the asthma gene?
Map location
Polymorphism
Expression pattern
Tissue
Autosomal dominant, 100% penetrance
…67% penetrance…
…33% penetrance
Number of people
Threshold model of susceptibility
healthy disease
gene —
gene +
Quantitative measure
Promoter
Missense
variants
Splice
site
Diversity
of
mutations
• altered protein function
variants
variants
• altered
transcription
• altered
transcript
Nonsense variants
UTR variants
• truncated transcript
• transcript instability
Intron variants
• regulatory elements
A gene mapper’s lunchbasket for an
excursion to multifactorial diseases
Population simulation
and disease modelling
Linkage analysis
Multilocus
association analysis
Etc.
Etc.
Etc.
Genetic factors in atopy and asthma
• population differences in the prevalence of
asthma are wide: 1.2%-6.2%
• twin studies show widely varying results:
• concordance in monozygotic twins
19%-88%
• concordance in dizygotic twins 4%-63%
• relative risk estimates vary between 1.3 and 6
• estimates of genetic component vary up to 87%
Genetic factors in adolescent asthma
Laitinen et al., Am J Respir Crit Care Med 157:1073, 1998
• Finnish population-based twin-family study
• 2483 twin families, participation rate 82-93%
Offspring
Mother
Father
Asthmatic
Healthy
Asthmatic
Healthy
Asthmatic
19 (11%)
103 (2.7%)
15 (10%)
107 (2.7%)
Healthy
157
3759
129
3787
Rate ratio
3.9
1.0
3.8
1.0
A brief population history
Little later
immigration
Small permanent
settlement of
south and west
coasts >2000 y
Population
movement in
the 1500’s
Rapid late
population
growth
(10 x / 250 y)
Population of Kainuu
1560-1574: about 200 houses
1577: estimated 1444 inhabitants
1609: estimated 1649 inhabitants
1626: estimated 2788 inhabitants
1641: estimated 1794 inhabitants
1654: estimated 2912 inhabitants
1860 : 25636 inhabitants (1.5% pop.)
1991: 52519 inhabitants (1.0% pop.)
Why study a multifactorial
disease in a founder isolate?
population
bottleneck
population
expansion
fewer
disease
loci and
alleles
time
15-20 generations
excess of founder haplotypes around susceptibility genes
Kainuu
Asthma Study
15-20 generations
Department of Medical Genetics and
Department of Pulmonary Diseases,
University of Helsinki and HUCH
Department of Clinical Genetics, the Finnish
Family Federation (Väestöliitto)
Kainuu Central Hospital, Kajaani
Disease gene mapping project
Design of study
Obtaining permissions
Recruitment of families
Verification of diagnoses
Collection of samples
Genotyping
Analysis of data
Identification of gene
Functional analysis
Utilization
Kainuu Asthma Study
Radio and newspaper advertisements
Probands contact the research group
Interview for entry criteria:
• physician-diagnosed asthma (self-reported)
• nuclear family willing to participate
• parents/grandparents born in Kainuu
Proband
• informed consent
• questionnaire and interview
• blood sample
Review of medical records
• verification of asthma diagnosis
Family members
• informed consent
• questionnaire
• blood sample
Verification of genealogy
• population records
Candidate gene regions in asthma
• Chromosome 5q31-q33
– Interleukin gene cluster —no gene implicated so far
• Chromosome 11q13, FCER1B
– Initial results on effect largely unconfirmed
• Chromosome 16p12, IL4R
– Replicated in several studies, small effect
• Xq28, IL9R
– Replicated in several studies, small effect
• Chromosome 19p13, FCER2
– Unconfirmed
• At least 12 other more or less uncertain localizations
Chromosome 5q31-q33
and Asthma in Finland
• a segment of about 28 cM spanning D5S404 to
D5S413 studied with 18 markers, including
candidate genes
• analysis of 51 sib-pairs and 26 cousin-pairs did not
suggest linkage of the segment to serum IgE values
• apparent haplotype associations are most likely due
to chance
• conclusion: serum IgE values controlled by loci other
than those in 5q31-q33 in the Finnish
Linkage results of the genome scan for asthma with 304 autosomal and 8 Xchromosomal markers in 86 Finnish pedigrees.
Laitinen et al., Nature Genetics 28:87, 2001
asthma
only
both
high IgE
only
Number of individuals
120
43%
102
37%
54
20%
Mean age at diagnosis
36
26
-
Mean age at sampling
47
36
43
Number of individuals
32
34%
48
51%
15
16%
Mean age at diagnosis
11
17
-
Mean age at sampling
26
32
42
A susceptibility gene for asthma in
chromosome 7p
• Genome scan in Finnish families gave significant
evidence for linkage to chromosome 7 (NPL=3.9 for
high IgE phenotype; NPL=3.0 for asthma)
• Result replicated in French-Canadian pedigrees from
Saguenay-Lac-St-Jean (NPL=2.7 for asthma)
• Second replication in North Karelian pedigrees
(NPL=1.9 for high IgE)
Laitinen et al., Nature Genetics 28:87, 2001
Association studies
Nr with
disease
Nr of
healthy
Nr of
subjects
Gene +
A
B
A+B
Gene —
C
D
C+D
Sum
A+C
B+D
A+B+C+D
A:(A+C)
Allele-specific risk =
B:(B+D)
Linkage disequilibrium mapping
Haplotypes
Marker
A
B
C
D
E
F
1
1
1
1
1
1
2
1
1
1
1
1
3
2
1
1
1
1
4
1
1
1
1
2
1
1
1
1
1
3
1
1
1
1
2
4
3
3
1
1
2
2
3
3
1
2
3
4
most
likely
location
for the
gene
Acknowledgements
Key group members
• Asthma: Tarja Laitinen,
Siru Mäkelä, Anne Polvi,
Johanna Vendelin
• Computational methods:
Päivi Onkamo, Petteri
Sevon, Vesa Ollikainen
Collaborators
• Asthma mapping: Lauri A.
Laitinen, Mark Daly, Tom
Hudson, Eric Lander
• Computational methods: Heikki
Mannila, Hannu T.T. Toivonen
• Gene expression: Riitta
Lahesmaa
One day I’ll
mutate…