Genetic mapping studies - Asthma and allergy
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Transcript of Genetic mapping studies - Asthma and allergy
Genetic mapping studies
- Asthma and allergy
Nature of disease gene projects
Clinical expertiseDiagnostic classification
Genetic analysisDisease 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?
Expression pattern
Polymorphism Tissue
Map location
Autosomal dominant, 100% penetrance
…67% penetrance…
…33% penetrance
gene — gene +
healthy disease
Num
ber
of p
eopl
e
Quantitative measure
Threshold model of susceptibility
Diversity of mutationsPromoter variants• altered transcription
Splice site variants • altered transcript
Missense variants• altered protein function
Nonsense variants• truncated transcript
Intron variants• regulatory elements
UTR variants• transcript instability
A gene mapper’s lunchbasket for an excursion to multifactorial diseases
Linkage analysis
Population simulation and disease modelling
Multilocus association analysis
Etc.
Etc.Etc.
Genetic factors in atopy and asthmaGenetic 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%
• 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 asthmaGenetic factors in adolescent asthma
• Finnish population-based twin-family study
• 2483 twin families, participation rate 82-93%
• Finnish population-based twin-family study
• 2483 twin families, participation rate 82-93%
Laitinen et al., Am J Respir Crit Care Med 157:1073, 1998Laitinen et al., Am J Respir Crit Care Med 157:1073, 1998
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
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
Little later immigration
Rapid late population
growth (10 x / 250 y)
Small permanent settlement of
south and west coasts >2000 y
Population movement in
the 1500’s
A brief population history
Population of KainuuPopulation 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?Why study a multifactorial disease in a founder isolate?
timetime
population bottleneckpopulation bottleneck
population expansionpopulation expansion
fewer disease loci and alleles
fewer disease loci and alleles
excess of founder haplotypes around susceptibility genesexcess of founder haplotypes around susceptibility genes
15-20 generations15-20 generations
15-20 generations15-20 generationsDepartment 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
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
Kainuu Asthma StudyKainuu Asthma Study
Disease gene mapping project
Recruitment of families Verification of diagnosesCollection of samples
GenotypingAnalysis of data
Design of studyObtaining permissions
Identification of geneFunctional analysis
Utilization
Kainuu Asthma StudyKainuu Asthma StudyRadio and newspaper advertisementsRadio and newspaper advertisements
Probands contact the research groupProbands contact the research groupInterview for entry criteria: • physician-diagnosed asthma (self-reported) • nuclear family willing to participate • parents/grandparents born in Kainuu
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
Proband • informed consent • questionnaire and interview • blood sample
Family members • informed consent • questionnaire • blood sample
Family members • informed consent • questionnaire • blood sample
Review of medical records • verification of asthma diagnosisReview of medical records • verification of asthma diagnosis
Verification of genealogy • population recordsVerification 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 FinlandChromosome 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
• 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 X-chromosomal markers in 86 Finnish pedigrees.
Laitinen et al., Nature Genetics 28:87, 2001
Number of individuals 32 48 15 34% 51% 16%
Mean age at diagnosis 11 17 -
Mean age at sampling 26 32 42
Number of individuals 32 48 15 34% 51% 16%
Mean age at diagnosis 11 17 -
Mean age at sampling 26 32 42
Number of individuals 120 102 54 43% 37% 20%
Mean age at diagnosis 36 26 -
Mean age at sampling 47 36 43
Number of individuals 120 102 54 43% 37% 20%
Mean age at diagnosis 36 26 -
Mean age at sampling 47 36 43
asthma high IgE only both only
asthma high IgE only both only
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 studiesNr 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
Allele-specific risk = A:(A+C)B:(B+D)
most likely location for the gene
most likely location for the gene
HaplotypesHaplotypesMarker
A B C D E F
Marker
A B C D E F
1 1 1 1 1 1
1 1 1 1 1 1
2 1 1 1 1 1
2 1 1 1 1 1
3 2 1 1 1 1
3 2 1 1 1 1
4 1 1 1 1 2
4 1 1 1 1 2
1 1 1 1 1 3
1 1 1 1 1 3
1 1 1 1 2 4
1 1 1 1 2 4
3 3 1 1 2 2
3 3 1 1 2 2
3 3 1 2 3 4
3 3 1 2 3 4
Linkage disequilibrium mapping
AcknowledgementsKey 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…