Background Allergic diseases (eczema, wheeze and rhinitis) in children often present as heterogeneous phenotypes. Understanding genetic associations of specific patterns of symptoms might facilitate understanding of the underlying biological mechanisms. Objective To examine associations between allergic disease‐related variants identified in a recent genome‐wide association study and latent classes of allergic diseases (LCADs) in two population‐based birth cohorts. Methods Eight previously defined LCADs between birth and 11 years: “No disease,” “Atopic march,” “Persistent eczema and wheeze,” “Persistent eczema with later‐onset rhinitis,” “Persistent wheeze with later‐onset rhinitis,” “Transient wheeze,” “Eczema only” and “Rhinitis only” were used as the study outcome. Weighted multinomial logistic regression was used to estimate associations between 135 SNPs (and a polygenic risk score, PRS) and LCADs among 6345 individuals from The Avon Longitudinal Study of Parents and Children (ALSPAC). Heterogeneity across LCADs was assessed before and after Bonferroni correction. Results were replicated in Manchester Asthma and Allergy Study (MAAS) (n = 896) and pooled in a meta‐analysis. Results We found strong evidence for differential genetic associations across the LCADs; pooled PRS heterogeneity P‐value = 3.3 × 10−14, excluding “no disease” class. The associations between the PRS and LCADs in MAAS were remarkably similar to ALSPAC. Two SNPs (a protein‐truncating variant in FLG and a SNP within an intron of GSDMB) had evidence for differential association (pooled P‐values ≤ 0.006). The FLG locus was differentially associated across LCADs that included eczema, with stronger associations for LCADs with comorbid wheeze and rhinitis. The GSDMB locus in contrast was equally associated across LCADs that included wheeze. Conclusions and clinical relevance We have shown complex, but distinct patterns of genetic associations with LCADs, suggesting that heterogeneous mechanisms underlie individual disease trajectories. Establishing the combination of allergic diseases with which each genetic variant is associated may inform therapeutic development and/or predictive modelling.
Background We have shown previously that current recommendations in UK guidelines for monitoring long-term conditions are largely based on expert opinion. Due to a lack of robust evidence on optimal monitoring strategies and testing intervals, the guidelines are unclear and incomplete. This uncertainty may underly variation in testing that has been observed across the UK between GP practices and regions. Methods Our objective was to audit current testing practices of GPs in the UK; in particular, perspectives on laboratory tests for monitoring long-term conditions, the workload, and how confident GPs are in ordering and interpreting these tests. We designed an online survey consisting of multiple-choice and open-ended questions that was promoted on social media and in newsletters targeting GPs practicing in UK. The survey was live between October–November 2019. The results were analysed using a mixed-methods approach. Results The survey was completed by 550 GPs, of whom 69% had more than 10 years of experience. The majority spent more than 30 min per day on testing (78%), but only half of the respondents felt confident in dealing with abnormal results (53%). There was a high level of disagreement for whether liver function tests and full blood counts should be done ‘routinely’, ‘sometimes’, or ‘never’ in patients with a certain long-term condition. The free text comments revealed three common themes: (1) pressures that promote over-testing, i.e. guidelines or protocols, workload from secondary care, fear of missing something, patient expectations; (2) negative consequences of over-testing, i.e. increased workload and patient harm; and (3) uncertainties due to lack of evidence and unclear guidelines. Conclusion These results confirm the variation that has been observed in test ordering data. The results also show that most GPs spent a significant part of their day ordering and interpreting monitoring tests. The lack of confidence in knowing how to act on abnormal test results underlines the urgent need for robust evidence on optimal testing and the development of clear and unambiguous testing recommendations. Uncertainties surrounding optimal testing has resulted in an over-use of tests, which leads to a waste of resources, increased GP workload and potential patient harm.
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