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Wheezing Phenotypes In Early Childhood In Two Large Birth Cohorts: ALSPAC and PIAMA Dr Raquel Granell Department of Social Medicine.

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Presentation on theme: "Wheezing Phenotypes In Early Childhood In Two Large Birth Cohorts: ALSPAC and PIAMA Dr Raquel Granell Department of Social Medicine."— Presentation transcript:

1 Wheezing Phenotypes In Early Childhood In Two Large Birth Cohorts: ALSPAC and PIAMA Dr Raquel Granell Department of Social Medicine

2 Asthma and wheezing phenotypes Asthma as a multiple disease entities Understanding wheezing phenotypes can help identify risk factors for asthma Martinez et al. (Tucson Children’s Respiratory Study, 1995) : 1.Non-atopic transient early wheezing in the first 3 years 2.Atopic Late-onset wheezing 3.IgE-mediated persistent wheezing

3 PART 1: Wheezing Phenotypes in ALSPAC (Thorax 2008) vs. Wheezing Phenotypes in PIAMA (JACI 2011)

4 ALSPAC 6-class model (Thorax 2008) N=6265 (complete data)

5 ALSPAC 6-class model (Thorax 2008) N=11678 (including missing cases)

6 PIAMA Prevention and Incidence of Asthma and Mite Allergy Multicentre birth cohort situated in The Netherlands Selected 4,146 pregnant women in 1996-1997 Data collected is very similar to ALSPAC

7

8 ALSPAC 6-class model N=6,265 (complete cases)

9 Associations of wheezing phenotypes with Asthma Outcomes at 8 years in ALSPAC and PIAMA OR (95%CI) for Doctor-diagnosed Asthma OR (95%CI) for Sensitization Mean difference (95%CI) for FEV1% pred. Ratio (95%CI) for BHR N/I1 (ref) TE 1.5 (0.9, 2.3) 5.4 (2.7, 11.0) PE IO LO P N=

10 Associations of wheezing phenotypes with Asthma Outcomes at 8 years in ALSPAC and PIAMA OR (95%CI) for Doctor-diagnosed Asthma OR (95%CI) for Sensitization Mean difference (95%CI) for FEV1% pred. Ratio (95%CI) for BHR N/I1 (ref) TE 1.5 (0.9, 2.3) 5.4 (2.7, 11.0) PE 9.6 (6.8, 13.7) - IO 372 (201, 686) 33 (15, 70) LO 30 (72, 102) 51 (22, 117) P 387 (246, 606) 72 (37, 140) N= 5201 2796

11 Associations of wheezing phenotypes with Asthma Outcomes at 8 years in ALSPAC and PIAMA OR (95%CI) for Doctor-diagnosed Asthma OR (95%CI) for Sensitization Mean difference (95%CI) for FEV1% pred. Ratio (95%CI) for BHR N/I1 (ref) TE 1.5 (0.9, 2.3) 5.4 (2.7, 11.0) 0.9 (0.7, 1.2) 1.3 (1.0, 1.7) PE 9.6 (6.8, 13.7) - 1.4 (1.0, 1.8) - IO 372 (201, 686) 33 (15, 70) 7.4 (4.8, 11.3) 5.1 (2.7, 9.8) LO 30 (72, 102) 51 (22, 117) 5.2 (3.8, 7.0) 4.2 (1.8, 9.9) P 387 (246, 606) 72 (37, 140) 4.8 (3.6, 6.4) 2.9 (1.7, 5.0) N= 5201 2796 3872 1432

12 Associations of wheezing phenotypes with Asthma Outcomes at 8 years in ALSPAC and PIAMA OR (95%CI) for Doctor-diagnosed Asthma OR (95%CI) for Sensitization Mean difference (95%CI) for FEV1% pred. Ratio (95%CI) for BHR N/I1 (ref) 0 (ref) TE 1.5 (0.9, 2.3) 5.4 (2.7, 11.0) 0.9 (0.7, 1.2) 1.3 (1.0, 1.7) -2.2 (-3.2, -1.2) -2.1 (-4.1, -0.1) PE 9.6 (6.8, 13.7) - 1.4 (1.0, 1.8) - -2.5 (-3.7, -1.2) - IO 372 (201, 686) 33 (15, 70) 7.4 (4.8, 11.3) 5.1 (2.7, 9.8) -4.5 (-6.8, -2.1) -2.9 (-6.8, 1.1) LO 30 (72, 102) 51 (22, 117) 5.2 (3.8, 7.0) 4.2 (1.8, 9.9) -3.1 (-4.8, -1.4) -2.3 (-7.2, 2.6) P 387 (246, 606) 72 (37, 140) 4.8 (3.6, 6.4) 2.9 (1.7, 5.0) -4.1 (-5.6, -2.5) -4.4 (-8.0, -0.8) N= 5201 2796 3872 1432 4106 871

13 Associations of wheezing phenotypes with Asthma Outcomes at 8 years in ALSPAC and PIAMA OR (95%CI) for Doctor-diagnosed Asthma OR (95%CI) for Sensitization Mean difference (95%CI) for FEV1% pred. Ratio (95%CI) for BHR N/I1 (ref) 0 (ref)1 (ref) TE 1.5 (0.9, 2.3) 5.4 (2.7, 11.0) 0.9 (0.7, 1.2) 1.3 (1.0, 1.7) -2.2 (-3.2, -1.2) -2.1 (-4.1, -0.1) 1.2 (1.0, 1.4) 1.3 (0.9, 1.8) PE 9.6 (6.8, 13.7) - 1.4 (1.0, 1.8) - -2.5 (-3.7, -1.2) - 1.5 (1.2, 1.8) - IO 372 (201, 686) 33 (15, 70) 7.4 (4.8, 11.3) 5.1 (2.7, 9.8) -4.5 (-6.8, -2.1) -2.9 (-6.8, 1.1) 4.7 (3.1, 7.2) 3.2 (1.6, 6.5) LO 30 (72, 102) 51 (22, 117) 5.2 (3.8, 7.0) 4.2 (1.8, 9.9) -3.1 (-4.8, -1.4) -2.3 (-7.2, 2.6) 3.8 (2.8, 5.2) 4.2 (1.8, 10) P 387 (246, 606) 72 (37, 140) 4.8 (3.6, 6.4) 2.9 (1.7, 5.0) -4.1 (-5.6, -2.5) -4.4 (-8.0, -0.8) 3.2 (2.4, 4.2) 3.6 (2.0, 6.7) N= 5201 2796 3872 1432 4106 871 2825 780

14 Conclusions part 1:  Five wheezing phenotypes were identified with longitudinal latent class analysis in PIAMA, comparable to the six previously found in ALSPAC  The existence of a novel, “intermediate onset” childhood wheezing phenotype was confirmed in independent analyses of data from the PIAMA cohort  Associations of wheezing phenotypes with asthma, atopy and lung function were remarkably similar in the two cohorts ACCEPTED

15 PART 2: Associations of Wheezing Phenotypes with Early Risk Factors in ALSPAC and PIAMA Perinatal characteristics Maternal age at delivery (years) Low birth weight (<2.5Kg) Preterm delivery (<37weeks) Caesarean section Postnatal characteristics Duration of breast feeding Maternal smoking during first year Day care attendance during first year Family pet ownership during first year Maternal anxiety during first year ┼ Demographic, maternal, pregnancy & child characteristics Overcrowding (>0.75 persons per room) Gas cooking Maternal lower education level Maternal history of asthma or allergy Maternal pre-pregnant BMI Mean (SD) Maternal smoking during pregnancy Maternal use of antibiotics during pregnancy Gender (male) Number of previous pregnancies Rented Housing ┼ Single mother ┼ Maternal anxiety at 32 weeks pregnancy ┼ ┼ Only available in ALSPAC

16 Demographic, maternal, pregnancy & child characteristics (I)

17 Perinatal characteristics (2) * Not adjusted for low birth weight (since low birth weight does not influence gestational age)

18 Postnatal characteristics (3)

19 Conclusions part 2 Phenotypes had similar patterns and strengths of associations with early environmental factors in both cohorts. Results suggest that prolonged early wheeze might be a severe sub-phenotype of transient early wheezing Male gender, prematurity, smoking during pregnancy, family history of asthma or allergy, previous pregnancies and daycare attendance were significantly associated with a higher risk of transient early wheeze.

20 Conclusions part 2 (cont.) Children with male gender, a family history of asthma or allergy and who did not receive breastfeeding for at least 3 months were more likely to have persistent wheeze.

21 PART 3 (ongoing work): Differential Associations between the Wheezing Phenotypes and Genetic Variants in Chromosome 17

22  Chromosome 17 is associated with childhood asthma (Nature Genetics 2010), particularly the region around ORMDL3 (Nature 2007)  We investigated the associations of wheezing phenotypes with all the variants in the region around ORMDL3  We found that this region is associated with intermediate onset, late onset and persistent wheezing but not with transient or prolonged early wheezing

23 Preliminary Results geneTEPEIOLOP IKZF30.95 (0.79, 1.13) p=0.53 1.11 (0.91, 1.36) p=0.29 1.39 (1.04, 1.86) p=0.028 1.21 (0.99, 1.48) p=0.068 1.58 (1.32, 1.90) p=7.73E-07 ZPBP20.97 (0.81, 1.15) p=0.69 1.11 (0.91, 1.35) p=0.3 1.36 (1.02, 1.82) p=0.037 1.23 (1.00, 1.50) p=0.045 1.58 (1.32, 1.89) p=9.02E-07 GSDMB0.99 (0.83, 1.17) p=0.87 0.90 (0.74, 1.09) p=0.28 0.69 (0.51, 0.92) p=0.012 0.81 (0.66, 0.99) p=0.043 0.63 (0.52, 0.75) p=5.69E-07 ORMDL30.92 (0.77, 1.10) p=0.36 0.85 (0.70, 1.04) p=0.11 0.66 (0.50, 0.89) p=0.006 0.79 (0.65, 0.97) p=0.025 0.63 (0.53, 0.76) p=7.44E-07 GSDMA0.95 (0.80, 1.13) p=0.6 0.94 (0.77, 1.14) p=0.55 0.68 (0.51, 0.91) p=0.009 0.69 (0.57, 0.84) p=0.0003 0.64 (0.53, 0.76) p=7.47E-07 PSMD30.91 (0.76, 1.09) p=0.31 1.02 (0.84, 1.25) p=0.82 1.68 (1.22, 2.31) p=0.002 1.41 (1.14, 1.75) p=0.002 1.70 (1.40, 2.07) p=1.32E-07 CSF31.09 (0.91, 1.30) p=0.33 0.98 (0.80, 1.21) p=0.88 0.62 (0.45, 0.85) p=0.003 0.71 (0.57, 0.88) p=0.002 0.58 (0.48, 0.71) p=9.50E-08 MED240.91 (0.76, 1.09) p=0.3 1.02 (0.83, 1.25) p=0.86 1.61 (1.17, 2.21) p=0.003 1.40 (1.13, 1.74) p=0.002 1.71 (1.41, 2.09) p=9.24E-08

24 Conclusions part 3 Strong evidence that SNPs in this chromosomal region are differentially associated with childhood wheezing phenotypes Can we use these genetic variants as markers to predict early childhood wheezing? What are the casual mechanism driving these associations? Can we identify risk groups by their genetic associations?  early intervention strategies for primary or secondary disease prevention?

25 Acknowledgements: Prof John Henderson Prof Jonathan Sterne Thanks for your attention! Raquel.Granell@bristol.ac.uk


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