Background

Oxidative stress related genes modify the effects of ambient air pollution or tobacco smoking on lung function decline. The impact of interactions might be substantial, but previous studies mostly focused on main effects of single genes.

Objectives

We studied the interaction of both exposures with a broad set of oxidative-stress related candidate genes and pathways on lung function decline and contrasted interactions between exposures.

Methods

For 12679 single nucleotide polymorphisms (SNPs), change in forced expiratory volume in one second (FEV1), FEV1 over forced vital capacity (FEV1/FVC), and mean forced expiratory flow between 25 and 75% of the FVC (FEF25-75) was regressed on interval exposure to particulate matter <10 µm in diameter (PM10) or packyears smoked (a), additive SNP effects (b), and interaction terms between (a) and (b) in 669 adults with GWAS data. Interaction p-values for 152 genes and 14 pathways were calculated by the adaptive rank truncation product (ARTP) method, and compared between exposures. Interaction effect sizes were contrasted for the strongest SNPs of nominally significant genes (pinteraction<0.05). Replication was attempted for SNPs with MAF>10% in 3320 SAPALDIA participants without GWAS.

Results

On the SNP-level, rs2035268 in gene SNCA accelerated FEV1/FVC decline by 3.8% (pinteraction = 2.5×10−6), and rs12190800 in PARK2 attenuated FEV1 decline by 95.1 ml pinteraction = 9.7×10−8) over 11 years, while interacting with PM10. Genes and pathways nominally interacting with PM10 and packyears exposure differed substantially. Gene CRISP2 presented a significant interaction with PM10 (pinteraction = 3.0×10−4) on FEV1/FVC decline. Pathway interactions were weak. Replications for the strongest SNPs in PARK2 and CRISP2 were not successful.

Conclusions

Consistent with a stratified response to increasing oxidative stress, different genes and pathways potentially mediate PM10 and tobacco smoke effects on lung function decline. Ignoring environmental exposures would miss these patterns, but achieving sufficient sample size and comparability across study samples is challenging.

Background

The nitric oxide (NO) pathway is involved in asthma, and eosinophils participate in the regulation of the NO pool in pulmonary tissues. We investigated associations between single nucleotide polymorphisms (SNPs) of NO synthase genes (NOS) and biological NO-related phenotypes measured in two compartments (exhaled breath condensate and plasma) and blood eosinophil counts.

Methodology

SNPs (N = 121) belonging to NOS1, NOS2 and NOS3 genes were genotyped in 1277 adults from the French Epidemiological study on the Genetics and Environment of Asthma (EGEA). Association analyses were conducted on four quantitative phenotypes: the exhaled fraction of NO (FeNO), plasma and exhaled breath condensate (EBC) nitrite-nitrate levels (NO2–NO3) and blood eosinophils in asthmatics and non-asthmatics separately. Genetic heterogeneity of these phenotypes between asthmatics and non-asthmatics was also investigated.

Principal Findings

In non-asthmatics, after correction for multiple comparisons, we found significant associations of FeNO levels with three SNPs in NOS3 and NOS2 (P≤0.002), and of EBC NO2–NO3 level with NOS2 (P = 0.002). In asthmatics, a single significant association was detected between FeNO levels and one SNP in NOS3 (P = 0.004). Moreover, there was significant heterogeneity of NOS3 SNP effect on FeNO between asthmatics and non-asthmatics (P = 0.0002 to 0.005). No significant association was found between any SNP and NO2–NO3 plasma levels or blood eosinophil counts.

Conclusions

Variants in NO synthase genes influence FeNO and EBC NO2–NO3 levels in adults. These genetic determinants differ according to asthma status. Significant associations were only detected for exhaled phenotypes, highlighting the critical relevance to have access to specific phenotypes measured in relevant biological fluid.

Background

Transient receptor potential (TRP) vanilloid and ankyrin cation channels are activated by various noxious chemicals and may play an important role in the pathogenesis of cough. The aim was to study the influence of single nucleotide polymorphisms (SNPs) in TRP genes and irritant exposures on cough.

Methods

Nocturnal, usual, and chronic cough, smoking, and job history were obtained by questionnaire in 844 asthmatic and 2046 non-asthmatic adults from the Epidemiological study on the Genetics and Environment of Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Occupational exposures to vapors, gases, dusts, and/or fumes were assessed by a job-exposure matrix. Fifty-eight tagging SNPs in TRPV1, TRPV4, and TRPA1 were tested under an additive model.

Results

Statistically significant associations of 6 TRPV1 SNPs with cough symptoms were found in non-asthmatics after correction for multiple comparisons. Results were consistent across the eight countries examined. Haplotype-based association analysis confirmed the single SNP analyses for nocturnal cough (7-SNP haplotype: p-global = 4.8 × 10-6) and usual cough (9-SNP haplotype: p-global = 4.5 × 10-6). Cough symptoms were associated with exposure to irritants such as cigarette smoke and occupational exposures (p < 0.05). Four polymorphisms in TRPV1 further increased the risk of cough symptoms from irritant exposures in asthmatics and non-asthmatics (interaction p < 0.05).

Conclusions

TRPV1 SNPs were associated with cough among subjects without asthma from two independent studies in eight European countries. TRPV1 SNPs may enhance susceptibility to cough in current smokers and in subjects with a history of workplace exposures.

Asthma is caused by a heterogeneous combination of environmental and genetic factors. In the context of GA2LEN (Global Allergy and Asthma European Network), we carried out meta-analyses of almost all genome-wide linkage screens conducted to date in 20 independent populations from different ethnic origins (≥3024 families with ≥10 027 subjects) for asthma, atopic asthma, bronchial hyper-responsiveness and five atopy-related traits (total immunoglobulin E level, positive skin test response (SPT) to at least one allergen or to House Dust Mite, quantitative score of SPT (SPTQ) and eosinophils (EOS)). We used the genome scan meta-analysis method to assess evidence for linkage within bins of traditionally 30-cM width, and explored the manner in which these results were affected by bin definition. Meta-analyses were conducted in all studies and repeated in families of European ancestry. Genome-wide evidence for linkage was detected for asthma in two regions (2p21–p14 and 6p21) in European families ascertained through two asthmatic sibs. With regard to atopy phenotypes, four regions reached genome-wide significance: 3p25.3–q24 in all families for SPT and three other regions in European families (2q32–q34 for EOS, 5q23–q33 for SPTQ and 17q12–q24 for SPT). Tests of heterogeneity showed consistent evidence of linkage of SPTQ to 3p11–3q21, whereas between-study heterogeneity was detected for asthma in 2p22–p13 and 6p21, and for atopic asthma in 1q23–q25. This large-scale meta-analysis provides an important resource of information that can be used to prioritize further fine-mapping studies and also be integrated with genome-wide association studies to increase power and better interpret the outcomes of these studies.

Background

The major factors individually reported to be associated with an increased frequency of CDKN2A mutations are increased number of patients with melanoma in a family, early age at melanoma diagnosis, and family members with multiple primary melanomas (MPM) or pancreatic cancer.

Methods

These four features were examined in 385 families with ⩾3 patients with melanoma pooled by 17 GenoMEL groups, and these attributes were compared across continents.

Results

Overall, 39% of families had CDKN2A mutations ranging from 20% (32/162) in Australia to 45% (29/65) in North America to 57% (89/157) in Europe. All four features in each group, except pancreatic cancer in Australia (p = 0.38), individually showed significant associations with CDKN2A mutations, but the effects varied widely across continents. Multivariate examination also showed different predictors of mutation risk across continents. In Australian families, ⩾2 patients with MPM, median age at melanoma diagnosis ⩽40 years and ⩾6 patients with melanoma in a family jointly predicted the mutation risk. In European families, all four factors concurrently predicted the risk, but with less stringent criteria than in Australia. In North American families, only ⩾1 patient with MPM and age at diagnosis ⩽40 years simultaneously predicted the mutation risk.

Conclusions

The variation in CDKN2A mutations for the four features across continents is consistent with the lower melanoma incidence rates in Europe and higher rates of sporadic melanoma in Australia. The lack of a pancreatic cancer–CDKN2A mutation relationship in Australia probably reflects the divergent spectrum of mutations in families from Australia versus those from North America and Europe. GenoMEL is exploring candidate host, genetic and/or environmental risk factors to better understand the variation observed.

We report a genome-wide association study of melanoma conducted by the GenoMEL consortium based on 317k tagging SNPs for 1650 genetically-enriched cases (from Europe and Australia) and 4336 controls and subsequent replication in 1149 genetically-enriched cases and 964 controls and a population-based case-control study of 1163 cases and 903 controls. The genome-wide screen identified five regions with genotyped or imputed SNPs reaching p < 5×10−7; three regions were replicated: 16q24 encompassing MC1R (overall p=2.54×10−27 for rs258322), 11q14-q21 encompassing TYR (p=2.41×10−14 for rs1393350) and 9p21 adjacent to MTAP and flanking CDKN2A (p=4.03×10−7 for rs7023329). MC1R and TYR are associated with pigmentation, freckling and cutaneous sun sensitivity, well-recognised melanoma risk factors, while the 9p21 locus is novel for common variants associated with melanoma. Despite wide variation in allele frequency, these genetic variants show notable homogeneity of effect across populations of European ancestry living at different latitudes and contribute independently to melanoma risk.

We conducted a genome-wide association pooling study for cutaneous melanoma and performed validation in samples totalling 2019 cases and 2105 controls. Using pooling we identified a novel melanoma risk locus on chromosome 20 (rs910873, rs1885120), with replication in two further samples (combined P <1 × 10-15). The odds ratio is 1.75 (1.53, 2.01), with evidence for stronger association in early onset cases.

SUMMARY

Asthma, allergic rhinitis (AR) and atopic dermatitis also called eczema are allergic co-morbidites which are likely to depend on pleiotropic genetic effects as well as on specific genetic factors. After a previous genome-wide linkage screen conducted for asthma and AR in a sample of 295 French EGEA families ascertained through asthmatic subjects, the aim here was to search for genetic factors involved in eczema and more particularly those ones shared by the three allergic diseases using the same EGEA data. In this sake, eczema and phenotypes of ‘allergic disease’ accounting for the joint information on the presence/absence of the three diseases were examined by linkage analyses using the Maximum Likelihood Binomial (MLB) method. A fine mapping was carried out in regions detected for potential linkage, followed by association studies using the Family Based Association Test (FBAT). Evidence for linkage to 11p14 region was shown for ‘allergic disease’ and eczema. Linkage was also indicated between eczema and 5q13 and between ‘allergic disease’ and both 5p15 and 17q21 regions. Fine mapping supported the evidence of linkage to 11p14 and FBAT analyses showed association between ‘allergic disease’ and a marker located at the linkage peak on 11p14. Further investigations in this region will allow identifying genetic factor(s) which could have pleiotropic effect in the three allergic diseases.

Polymorphisms in ADAM33, the first gene identified in asthma by positional cloning, have been recently associated with psoriasis. No replication study of this association has been published so far. Data available in the French EGEA study (Epidemiological study on Genetics and Environment of Asthma, bronchial hyperresponsivensess and Atopy) give the opportunity to attempt to replicate the association between ADAM33 and psoriasis in 2002 individuals. Psoriasis (n = 150) has been assessed by questionnaire administered by an interviewer and a sub-sample of subjects with early-onset psoriasis (n = 74) has been identified based on the age of the subjects at time of interview (<40 years). Nine SNPs in ADAM33 and 11 SNPs in PSORS1 were genotyped. Association analysis was conducted by using two methods, GEE regression-based method and a likelihood-based method (LAMP program). The rs512625 SNP in ADAM33 was found associated with psoriasis at p = 0.01, the usual threshold required for replication (OR [95% CI] for heterozygotes compared to the reference group of homozygotes for the most frequent allele = 0.61 [0.42;0.89]). The rs628977 SNP, which was not in linkage disequilibrium with rs512625, was significantly associated with early-onset psoriasis (p = 0.01, OR [95% CI] for homozygotes for the minor allele compared to the reference group = 2.52 [1.31;4.86]). Adjustment for age, sex, asthma and a PSORS1 SNP associated with psoriasis in the EGEA data did not change the significance of these associations. This suggests independent effects of ADAM33 and PSORS1 on psoriasis. This is the first study that replicates an association between genetic variants in ADAM33 and psoriasis. Interestingly, the 2 ADAM33 SNPs associated with psoriasis in the present analysis were part of the 3-SNPs haplotypes showing the strongest associations in the initial study. The identification of a pleiotropic effect of ADAM33 on asthma and psoriasis may contribute to the understanding of these common immune-mediated diseases.

Genome-wide association studies raise study-design and analytical issues that are still being debated. Among them, stands the issue of reducing the number of markers to be genotyped without loss of efficiency in identifying trait loci, which can reduce the cost of studies and minimize the multiple testing problem. With this aim, we proposed a two-step strategy based on two analytical methods suited to examine sets of markers rather than single markers: the local score, which screens the genome to select candidate regions in Step 1, and FBAT-LC, a multiple-marker family-based association test used to obtain significance levels of regions at step 2. The performance of this strategy was evaluated on all replicates of Genetic Analysis Workshop 15 Problem 3 simulated data, using the answers to that problem. Overall, seven of the nine generated trait loci were detected in at least 87% of the replicates using a framework designed to handle either association with the disease or association with the severity of disease. This multiple-marker strategy was compared to the single-marker approach. By considering regions instead of single markers, this strategy minimizes the multiple testing problem and the number of false-positive results.

Background

Genetic studies of complex disorders such as hypertension often utilize families selected for this outcome, usually with information obtained at a single time point. Since age-at-onset for diagnosed hypertension can vary substantially between individuals, a phenotype based on long-term follow up in unselected families can yield valuable insights into this disorder for the general population.

Methods

Genetic analyses were conducted using 2884 individuals from the largest 330 families of the Framingham Heart Study. A longitudinal phenotype was constructed using the age at an examination when systolic blood pressure (SBP) first exceeds 139 mm Hg. An interval for age-at-onset was created, since the exact time of onset was unknown. Time-fixed (sex, study cohort) and time-varying (body mass index, daily cigarette and alcohol consumption) explanatory variables were included.

Results

Segregation analysis for a major gene effect demonstrated that the major gene effect parameter was sensitive to the choice for age-at-onset. Linkage analyses for age-at-onset were conducted using 1537 individuals in 52 families. Evidence for putative genes identified on chromosome 17 in a previous linkage study using a quantitative SBP phenotype for these data was not confirmed.

Conclusions

Interval censoring for age-at-onset should not be ignored. Further research is needed to explain the inconsistent segregation results between the different age-at-onset models (regressive threshold and proportional hazards) as well as the inconsistent linkage results between the longitudinal phenotypes (age-at-onset and quantitative).