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…