Meta-analysis of genome-wide linkage studies of asthma and related traits

1465-9921-9-38 RRJ Research Meta-analysis of genome-wide linkage studies of asthma and related traits Denham Samuel mzyysnd@exmail.nottingham.ac.uk Koppelman H Gerard g.h.koppelman@bkk.umcg.nl Blakey John John.Blakey@nottingham.ac.uk Wjst Matthias m@wjst.de Ferreira A Manuel mferreira@chgr.mgh.harvard.edu Hall P Ian Ian.Hall@nottingham.ac.uk Sayers Ian ian.sayers@nottingham.ac.uk

Division of Therapeutics & Molecular Medicine, University Hospital of Nottingham, Nottingham, UK

Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, The Netherlands

Institute of Epidemiology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany

Center for Human Genetic Research, Massachusetts General Hospital, Boston, USA

Respiratory Research 1465-9921 2008 9 1 38 http://respiratory-research.com/content/9/1/38 18442398 10.1186/1465-9921-9-38 10 12 2007 28 4 2008 28 4 2008 2008 Denham et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Asthma and allergy are complex multifactorial disorders, with both genetic and environmental components determining disease expression. The use of molecular genetics holds great promise for the identification of novel drug targets for the treatment of asthma and allergy. Genome-wide linkage studies have identified a number of potential disease susceptibility loci but replication remains inconsistent. The aim of the current study was to complete a meta-analysis of data from genome-wide linkage studies of asthma and related phenotypes and provide inferences about the consistency of results and to identify novel regions for future gene discovery.

Methods

The rank based genome-scan meta-analysis (GSMA) method was used to combine linkage data for asthma and related traits; bronchial hyper-responsiveness (BHR), allergen positive skin prick test (SPT) and total serum Immunoglobulin E (IgE) from nine Caucasian asthma populations.

Results

Significant evidence for susceptibility loci was identified for quantitative traits including; BHR (989 pedigrees, n = 4,294) 2p12-q22.1, 6p22.3-p21.1 and 11q24.1-qter, allergen SPT (1,093 pedigrees, n = 4,746) 3p22.1-q22.1, 17p12-q24.3 and total IgE (729 pedigrees, n = 3,224) 5q11.2-q14.3 and 6pter-p22.3. Analysis of the asthma phenotype (1,267 pedigrees, n = 5,832) did not identify any region showing genome-wide significance.

Conclusion

This study represents the first linkage meta-analysis to determine the relative contribution of chromosomal regions to the risk of developing asthma and atopy. Several significant results were obtained for quantitative traits but not for asthma confirming the increased phenotype and genetic heterogeneity in asthma. These analyses support the contribution of regions that contain previously identified asthma susceptibility genes and provide the first evidence for susceptibility loci on 5q11.2-q14.3 and 11q24.1-qter.

Background

Asthma is a disease characterised by recurrent respiratory symptoms, reversible variable airway obstruction, airway inflammation and increased bronchial hyper-responsiveness 1. Estimates suggest that 100–150 million people worldwide have asthma. Atopy is a predisposition towards the development of immediate hypersensitivity against common environmental antigens. Atopy and asthma are closely related, however they are not interchangeable. Most asthmatic individuals are atopic but atopic individuals may not have asthmatic symptoms. Asthma and atopic disease show strong familial aggregation and heritability estimates vary between 36–79% 2. A greater understanding of the genetic basis of asthma and atopy holds great promise for the identification of novel therapeutic targets.

Linkage analysis using short tandem repeats or microsatellites to follow the transfer of genetic information between generations has been used to identify chromosomal regions that potentially contain asthma and atopy susceptibility genes. Commonly sub-phenotypes of clinical relevance are used including; elevated total Immunoglobulin E (IgE) levels, atopy defined by positive skin prick test to one or more allergen or elevated specific IgE and bronchial hyper-responsiveness (BHR) 3. These studies have identified linkage on multiple chromosomal regions e.g. 2q22-33, 5q31.1-33, 6p21.3, 11q13, 12q14.3-24.1, 13q14, 14q11.2-13 and 19q13; however replication of linkage findings has been limited 3. Low statistical power and the potential for type I and type II errors may explain these findings. Combining data has the potential to provide inferences about the consistency of results across studies and to identify regions that contain asthma and atopy susceptibility genes.

The aim of the current study was to complete the first meta-analysis of available genome wide linkage data for asthma and related traits (asthma per se, BHR, total IgE, allergen skin prick test response (SPT)) in the Caucasian population using the Genome Scan Meta Analysis (GSMA) method 4. GSMA is a non parametric, rank based approach and has been used extensively in other disorders e.g. schizophrenia 5.

Methods

Systematic Literature Search

To identify published studies for inclusion in the GSMA of asthma and related phenotypes we completed a systematic literature review in September 2006. We used PubMed and the following search string (Asthma OR BHR OR bronchial hyper responsiveness OR bronchial hyperreactivity OR AHR OR airway hyper responsiveness OR respiratory hypersensitivity OR histamine OR slope OR methacholine OR atopy OR atopic OR dermatitis, atopic OR IgE OR immunoglobulin E OR SPT OR skin prick tests OR skin tests) AND linkage AND genome-scan OR scan OR genome OR genomewide OR genome-wide OR LOD OR microsatellite). Limits were set on the search including; published in English, human studies, published 1996–2006 and the exclusion of reviews. This initial search identified 516 matches of which 488 were discarded as not containing genome-wide linkage data. A further eight studies were discarded as they were in non-Caucasian populations and we wished to avoid any population stratification issues leaving 20 potential Caucasian studies for inclusion. Genome-wide linkage analyses for asthma related traits in the Hutterite Founder population 6 was not included in the current analyses as limited data was available and the focus of the present study was Caucasian out-bred populations.

Of the 20 manuscripts identified a further nine were removed from the analyses for a combination of the following reasons; the study was superseded by another including the families from the original, LOD score plots in the manuscript were not labelled and/or unreadable, no genome-wide data was presented e.g. in the manuscript describing the positional cloning of ADAM33, linkage analyses in 460 families for asthma, IgE and BHR phenotypes were performed but has never been published in full 7 or the phenotypes studied did not meet our criteria. All authors were contacted and invited to provide complete datasets.

Phenotype definition and study inclusion/exclusion

There was a large degree of heterogeneity in phenotype definitions and so these were standardised for inclusion. Asthma was defined using doctor diagnosis and/or currently taking asthma medication, however we did include data from the Dutch population which used an algorithm based on asthma symptoms, the presence of BHR, reversibility to β₂-adrenergic receptor agonist and smoking history to define asthma 8. Analyses were completed with and without the Dutch families. Total IgE levels were analysed in the genome scans using quantitative data generated by Pharmacia CAP system 9, Pharmacia IgE EIA 10, Phadebas PRIST 11 and ELISA techniques 1213 which have shown good inter assay correlation 1415, therefore all studies were included. Positive skin prick response to one or more allergen was used as a marker of atopy and for inclusion in the GSMA. However, allergens used in each study varied; Dermatphagoides pteronyssinus, mixed grass pollen 9, Dermatphagoides pteronyssinus, Cladosporium herbarum, Alternaria tenuis, timothy grass, olive, birch, Parieteria judaica, ragweed, Aspergillus, Blatella Germancia 11, mixed grass and tree pollens, mixed weeds, Dermatphagoides pteronyssinus, dog, cat, a mixture of guinea pig and rabbit, horse, Aspergillus fumigatus, Alternaria alternate 10, house dust mite 12, Dermatphagoides pteronyssinus and 10 others 13 and Dermatphagoides pteronyssinus, D. farinae, dog, cat, grass mix, pollen and alternaria 16. BHR was measured in multiple ways using different provocation stimuli e.g. histamine or methacholine providing categorical and/or quantitative analyses. These provocation stimuli have shown a significant correlation (r = 0.95) in the responses induced 17, however it is worth noting that this has not been reproduced in all studies. Studies with BHR data were included in the GSMA irrespective of the criteria used in the original manuscript.

Genome Scan Meta Analysis (GSMA)

GSMA was used as it is able to combine linkage data from studies with different marker sets and analysed by different methods including permutated p-values. GSMA was implemented using GSMA software 4518. Briefly, the genome was divided into 120 bins of approximately 30 cM, for each study the maximum evidence for linkage e.g. LOD score or p-value was identified for each bin and these bins were then ranked relative to their evidence for linkage in that study. These ranks were summed across studies and the summed rank (SR) forms the basis of the test statistic 4. An ordered rank (OR) statistic was also generated which gives a genome wide interpretation of significance by comparing the n-th highest summed rank with the distribution of the n-th highest summed ranks obtained through simulation 5. We completed an unweighted and weighted analyses using information content (√(no. pedigrees × no. markers)) as a weighting factor.

Statistical Significance

Simulation studies have shown that any bin with a p(SR) < 0.05 and a p(OR) < 0.05 has a high probability of containing a true susceptibility gene 5. Applying Bonferroni correction a p < 0.000417 provides evidence for genome wide significance for linkage and a p < 0.0083 provides suggestive evidence for linkage 5.

Results

Data included

The selection criteria and data requests provided eleven studies of nine Caucasian asthma populations for our analyses (Table 1) including data from 1,267 pedigrees (n = 5,832) for asthma (80.2% of pedigrees available in the public domain or following request, missing 249 19 and 65 pedigrees 20), 989 pedigrees (n = 4,294) for BHR (79.9% of available, missing 249 pedigrees 19), 1,093 pedigrees (n = 4,746) for SPT (81.5% of available, missing 249 pedigrees 19) and 729 pedigrees (n = 3,224) for total IgE (65.9% of available, missing 249 19, and 129 pedigrees 21).

Table 1

Characteristics of genome-wide linkage studies included in the GSMA

NUMBER OF.^(b)

COHORT (REF.)

PHENOTYPES^(a)

PED. (AFF/IND.)

MKS.

WF.

MKR MAP (SP.)^(c)

STUDY TYPE^(d)

ANALYSIS PROGRAM

INCLUDED IN GSMA

Australian [9]

B: Slope (-,0–12 μmol meth.)

80 (25/364)

253

142.267

- (10 cM)

Nonpar.two.

B: 23 p-values < 0.05

I: Quantitative

I: 21 p-values < 0.05

S: 2 allergens

S: 19 p-values < 0.05

CSGA [33]

A: Quest./Doc diag

79 (200/316)

360

168.642

Marshfield (10 cM)

Nonpar. multi.

Modified GENEHUNTER

A: LOD scores from graphs

German [34]

B: PD₂₀(Neb, < 8 mg/ml meth.)

97 (200/415)

333

179.725

Modified Genethon (10.7 cM)

Nonpar. multi.

GENEHUNTER, MAP-MAKER/SIBS

B: Complete dataset

French [11]

A: Quest./Meds.

46 (102/210)

254

108.093

– (13 cM)

Nonpar. multi.

GENEHUNTER, SIBPAIR

A: 11 p-values

B: Slope (-, meth.)

B: 8 p-values

I: Quantitative

I: 8 p-values

S: 11 allergens

S: 19 p-values

Icelandic [35]

A: Doc diag./Meds.

175 (596/1134)

976*

413.280

Decode (4 cM)

Nonpar. multi.

ALLEGRO

A: LOD scores from graphs

Dutch [10, 36, 37]

A: Algorithm

200 (-/1159)

366

270.555

Marshfield Weber v8 (10 cM)

Nonpar.

SOLAR, GENEHUNTER

A: Complete dataset

B: PD₂₀(-, < 32 mg/ml hist.)

B: Complete dataset

I: Quantitative

I: Complete dataset

S: 16 allergens

S: Complete dataset

German [12]

A: Doc diag.

201 (506/867)

364

270.489

Modified Genethon (10 cM)

Nonpar. multi.

MERLIN

A: Complete dataset

I: Quantitative/Catagorical

I: Complete quantitative dataset

S: HDM+

S: Complete dataset

Australian [13]

A: Quest./Meds.

202 (169/591)

624

355.032

- (7.1 cM)

Nonpar. multi.

MERLIN, SOLAR

A: Complete dataset

B: PD₂₀(-, < 7.8 μmol hist)

B: Complete dataset

I: Quantitative

I: Complete dataset

S: 11 allergens.

S: Complete dataset

GAIN [16]

A: Doc diag.

364 (1014/1555)

396*

379.663

Decode (-)

Nonpar. multi.

MERLIN

A: LOD scores from graphs

B: PD₂₀(-, < 8 mg/ml meth.)

B: LOD scores from graphs

S: 7 allergens

S: LOD scores from graphs

(a) A = asthma; B = bronchial hyper-responsiveness (Neb = nebuliser, Dos = dosimeter); I = total serum IgE; S = skin prick test response; Quest = questionnaire; Doc diag = doctor diagnosis; Meds = asthma medication; Meth = methacholine; Hist = histamine; HDM = house dust mite; PD₂₀= provocation dose resulting in a 20% fall in FEV₁. (b) Ped = total genotyped pedigrees; AFF = total genotyped asthmatic cases, Ind = total genotyped individuals; Mks = total autosomal microsatellite markers; Wt = weighting factor. (c) Sp = average marker spacing. (d) Nonpar = nonparametric; Two = two point; Multi = multipoint. (-) = not provided, *number of autosomal markers not given, total number used for weighting.

Asthma

The weighted asthma analyses did not identify any chromosomal region with a p(SR) and p(OR) < 0.05 (Figure 1 and Table 2). No bin p(SR) met genome wide significance (p < 0.000417) or suggestive evidence for linkage (p < 0.0083) in these analyses however three regions demonstrated a p(SR) < 0.05; 6p22.3-p21.1, 10p14-q11.21 and 12q24.31-qter (Table 2). Eight regions met suggestive linkage criteria in the ordered rank analyses; 1p31.1-p13.3, 2p12-q22.1, 4p14-q13.3, 7q34-qter, 12pter-p12,1, 12p12.1-p11.21, 14q32.12-qter, 17pter-p12 and 20pter-p12.3 (Table 2). Analyses of the asthma phenotype using unweighted GSMA generated similar findings to the weighted analyses (Figure 2). To confirm that the inclusion of the Dutch linkage data for the asthma phenotype (defined by algorithm) had not confounded the analyses we completed GSMA without these data focusing on doctor diagnosed asthma only (1,067 pedigrees). Again, no chromosomal region with a p(SR) and p(OR) < 0.05 was identified (data not shown).

Figure 1

p(SR) & p(OR) in weighted GSMA

p(SR) & p(OR) in weighted GSMA. A. asthma. B. bronchial hyper-responsiveness. C. total serum IgE. D. skin prick test response. A p(SR) of p < 0.000417 = significant linkage, p < 0.0083 = suggestive linkage. p(SR) & p(OR) data were transformed using f(x) = 0.05/x and plotted on a log₁₀scale to improve clarity.

Table 2

Weighted GSMA for Asthma (1,267 pedigrees, n = 5,832)

PROBABILITY

BIN^(a)

GENETIC LOCUS^(b)

DISTANCE (cM)^(c)

PHYSICAL POSITION (KB)^(d)

SUMMED RANK (SR)

p(SR)

p(OR)

1pter-p36.23

0.00–20.61

pter-9332

376.576

0.68121

0.03775

1p31.1-p13.3

113.69–142.24

82867–110103

346.834

0.78259

0.00718*

1q31.1-q32

201.58–231.11

185232–210150

347.872

0.77937

0.02791

2p12-q22.1

101.56–128.41

79617–119705

341.174

0.79974

0.00694*

2q31.1-q34

177.53–206.74

172805–212021

317.985

0.86170

0.03548

2q35-qter

233.62–269.07

230618-qter

316.169

0.86603

0.00908

3p14.1-q12.3

88.60–117.76

64182–103187

612.921

0.02348

0.80059

4p14-q13.3

51.60–78.97

38279–72275

343.939

0.79152

0.00714*

4q28.3-q32.1

134.74–159.30

137492–160828

346.992

0.78212

0.01609

6pter-p22.3

0.00–32.62

pter-16854

383.747

0.65433

0.03220

6p22.3-p21.1

32.62–65.14

16854–43207

592.740

0.03905

0.72593

7p21.1-p14.1

29.28–59.93

19430–40230

317.779

0.86218

0.01583

7q31.1-q34

122.48–148.11

75216–138638

381.650

0.66230

0.03107

7q34-qter

148.11–181.97

138638-qter

313.741

0.87152

0.00536*

8pter-p22

0.00–27.40

pter-13111

376.368

0.68196

0.01899

8q22-q24.21

110.2–137.92

99237–127416

365.804

0.71999

0.02820

8q24.21-qter

137.92–167.90

127416-qter

373.141

0.69378

0.02636

9p22.3-p21.1

27.32–53.60

14264–29850

349.926

0.77291

0.03321

10p14-q11.21

29.15–62.23

10591–36230

635.659

0.01229

0.79026

11p12-q13.3

47.06–72.82

36450–70234

353.473

0.76155

0.02578

12pter-p12.1

0.00–24.45

pter-11686

299.278

0.90180

0.00570*

12p12.1-p11.21

24.45–53.28

11686–32879

292.228

0.91466

0.00766*

12q24.31-qter

139.61–170.60

120806-qter

607.388

0.02714

0.65821

13q22.2-q33.1

58.54–85.41

74875–102346

354.469

0.75831

0.04007

14pter-q13.1

0.00–40.11

pter- 33529

362.366

0.73182

0.03622

14q32.12-qter

105.00-138.18

90647-qter

305.539

0.88932

0.00423*

101

17pter-p12

0.00–25.14

pter-11325

312.768

0.87374

0.00213*

105

18pter-p11

0.00–24.08

pter- 7462

377.842

0.67650

0.04965

113

20pter-p12.3

0.00–21.15

pter-7608

339.111

0.80587

0.00524*

114

20p12.3-p11

21.15–47.52

7608–21259

282.935

0.92982

0.01324

Chromosomal regions with a p(SR) or p(OR) < 0.05 are shown. ^aBin number from GSMA (1–120 inclusive). ^bCytogenetic band (Taken from April 2002 Genome Browser, UCSC). ^cGenetic distance in Marshfield cM (not cumulative). ^dPhysical position in kilobase pairs (Taken from December 2006 UniSTS, NCBI/Genome Browser, UCSC). *p < 0.000417 = Genome wide significance for linkage, p < 0.0083 = Suggestive for linkage [5].

Figure 2

p(SR) & p(OR) in unweighted GSMA

p(SR) & p(OR) in unweighted GSMA. A. asthma. B. bronchial hyper-responsiveness. C. total serum IgE. D. skin prick test response. A p(SR) of p < 0.000417 = significant linkage, p < 0.0083 = suggestive linkage. p(SR) & p(OR) data were transformed using f(x) = 0.05/x and plotted on a log₁₀scale to improve clarity.

Bronchial Hyper-responsiveness

The weighted BHR analyses strongly suggested that 6p22.3-p21.1 contains BHR susceptibility gene(s) as a p(SR) and p(OR) < 0.05 was observed (p = 0.007, p = 0.049 respectively (Figure 1 and Table 3)). Two other regions showed suggestive evidence (p < 0.0083) for linkage to the BHR phenotype; 2p12-q22.1 (p(SR) = 0.006) and 11q24.1-qter (p(SR) = 0.005). In the unweighted analyses three regions showed evidence for linkage (p(SR) and p(OR) ≤ 0.05), i.e. 2q22.1-q23.3, 7q12.11-q31.1 and 5q23.2-q34 (Figure 2).

Table 3

Weighted GSMA for bronchial hyper-responsiveness (989 pedigrees, n = 4,294)

PROBABILITY

BIN^(a)

GENETIC LOCUS^(b)

DISTANCE (cM)^(c)

PHYSICAL POSITION (KB)^(d)

SUMMED RANK (SR)

p(SR)

p(OR)

2p16.2-p12

76.34–101.56

54063–79617

532.855

0.02751

0.22094

2p12-q22.1

101.56–128.41

79617–119705

576.585

0.00574*

0.14743

2q22.1-q23.3

128.41–154.48

119705–151529

518.593

0.04085

0.08859

5q23.2-q34

131.48–164.19

123774–162087

551.701

0.01511

0.09586

6p22.3-p21.1

32.62–65.14

16854–43207

571.381

0.00716*

0.04861

7p21.1-p14.1

29.28–59.93

19430–40230

523.367

0.03597

0.24658

7p14.1-q21.11

59.93–91.67

40230–81002

518.746

0.04070

0.19114

7q21.11-q31.1

91.67–122.48

81002–109766

461.380

0.13926

0.02065

8q13.1-q22

82.84–110.20

67744–99237

468.188

0.12312

0.04443

11q13.3-q22.3

72.82–98.98

70185–103732

465.589

0.12913

0.01652

11q24.1-qter

123.00–147.77

122977-qter

579.520

0.00505*

0.46485

13q13.2-q22.2

26.87–58.54

33636–74875

472.999

0.11255

0.03312

111

19q12-q13.33

52.59–75.41

35843–54589

460.759

0.14078

0.01070

115

20p11-q13.13

47.52–72.27

21259–46747

476.308

0.10563

0.03503

116

20q13.13-qter

72.27–101.22

46747-qter

467.593

0.12448

0.02343

Positive allergen skin prick test

Weighted analyses of the SPT phenotype identified two regions that had a p(SR) and p(OR) ≤ 0.05 strongly suggesting these regions are susceptibility loci (Figure 1 and Table 4). These regions are 17p12-q24.3 (two adjacent bins, 17p12-q21.33 p(SR) = 0.00043, p(OR) = 0.050 and 17q21.33-q24.3 p(SR) = 0.047, p(OR) = 0.038) and region 3p22.1-q22.1 (three adjacent bins, 3p22.1-p14.1 p(SR) = 0.045, p(OR) = 0.063, 3p14.1-q12.3 p(SR) = 0.003, p(OR) = 0.0045 and 3q12.3-q22.1 p(SR) = 0.00084, p(OR) = 0.00406). The analyses of the unweighted SPT datasets identified chromosomes 3 and 17 as containing the major determinants (Figure 2).

Table 4

Weighted GSMA for skin prick test response (1,093 pedigrees, n = 4,746)

PROBABILITY

BIN^(a)

GENETIC LOCUS^(b)

DIST. (cM)^(c)

PHYS POS. (KB)^(d)

SUMMED RANK (SR)

p(SR)

p(OR)

1p13.3-q23.3

142.24–170.84

110103–159125

541.271

0.02081

0.22906

3p22.1-p14.1

63.12–88.60

38845–64182

513.869

0.04488

0.06344

3p14.1-q12.3

88.60–117.76

64182–103187

591.392

0.00298*

0.00450

3q12.3-q22.1

117.76–146.60

103187–134474

614.373

0.00084*

0.00406

6p21.1-q15

65.14–99.01

43207–90985

521.717

0.03654

0.12598

6q15-q23.2

99.01–131.07

90985–132584

525.276

0.03318

0.18839

11q22.3-q24.1

98.98–123.00

103732–122977

515.746

0.04276

0.11460

102

17p12-q21.33

25.14–63.62

11325–39726

624.777

0.00043*

0.05044

103

17q21.33-q24.3

63.62–93.98

39726–66600

511.187

0.04799

0.03824

108

18q22.1-qter

96.48–126.00

60025-qter

209.839

0.96132

0.03480

118

21q21.3-qter

25.26–57.77

27903-qter

528.536

0.03029

0.28738

Total Immunoglobulin E

Weighted analyses of the IgE phenotype strongly suggested 5q11.2-q14.3 (p(SR) = 0.031, p(OR) = 0.060) and 6pter-p22.3 (p(SR) = 0.033, p(OR) = 0.026) contain genes that influence IgE levels (Figure 1 and Table 5). The region adjacent to 6pter-p22.3, i.e. 6p22.3-p21.1 has a p(SR) = 0.00999 approaching suggestive linkage providing further evidence for this region. Analyses of the IgE phenotype using the unweighted GSMA showed similar overall findings (Figure 2).

Table 5

Weighted GSMA for total serum IgE (729 pedigrees, n = 3,224)

PROBABILITY

BIN^(a)

GENETIC LOCUS^(b)

DIST. (cM)^(c)

PHYS POS. (KB)^(d)

SUMMED RANK (SR)

p(SR)

p(OR)

1p36.23-p35.3

20.61–54.30

9332 – 24723

476.251

0.01171

0.41867

1q23.3-q31.1

170.84–201.58

159125–185232

450.659

0.03099

0.14664

5q11.2-q14.3

64.14–97.82

55758–88765

450.303

0.03127

0.06031

5q23.2-q34

131.48–164.19

123774–162087

464.611

0.01890

0.40276

6pter-p22.3

0.00–32.62

pter-16854

448.903

0.03276

0.02583

6p22.3-p21.1

32.62–65.14

16854–43207

479.723

0.00999

0.71984

7p21.1-p14.1

29.28–59.93

19430–40230

454.706

0.02708

0.41494

11q13.3-q22.3

72.82–98.98

70185–103732

453.763

0.02792

0.22926

Multiple phenotype analyses

In addition to the primary phenotype analyses we investigated overlapping chromosomal regions containing genetic determinants of asthma and asthma related traits consistent with gene(s) having pleiotrophic effects in asthma and allergy (Table 6). Interestingly, region 6p22.3-p21.1 which contains the HLA region showed a p(SR) < 0.05 in the asthma, BHR and IgE analyses potentially as expected due to the role of HLA restriction in many immunological mechanisms. Several other regions also showed overlapping concordance, in particular regions; 3p14.1-q12.3 (asthma, SPT), 5q23.2-q34 (asthma, BHR, IgE) and 7p21.1-14.1 (asthma, BHR, IgE).

Table 6

Overlapping chromosomal regions in weighted GSMA for asthma, and the three intermediate phenotypes

ASTHMA

BHR

TOTAL IGE

SPT RESPONSE

BIN^(a)

GENETIC LOCUS^(b)

DIST. (cM)^(c)

PHYS POS. (KBp)^(d)

p(SR)

p(OR)

p(SR)

p(OR)

p(SR)

p(OR)

p(SR)

p(OR)

1p13.3-q23.3

142.24–170.84

110103–159125

0.06630

0.13155

0.02081

0.22906

1q23.3-q31.1

170.84–201.58

159125–185232

0.03099

0.14664

0.08924

0.13402

2p12-q22.1

101.56–128.41

79617–119705

0.79974

0.00694

0.00574*

0.14743

3p14.1-q12.3

88.60–117.76

64182–103187

0.02348

0.80059

0.09312

0.17837

0.00298

0.00450*

5q5q14.3-q23.2

97.82–131.48

88765–123774

0.71879

0.05004

0.09195

0.08596

5q23.2-q34

131.48–164.19

123774–162087

0.06027

0.77886

0.01511

0.09586

0.01890

0.40276

6pter-p22.3

0.00–32.62

pter-16854

0.65433

0.03220

0.03276

0.02583