Background28 Allergic diseases (eczema, wheeze and rhinitis) in children often present as heterogeneous phenotypes.29 Understanding genetic associations of specific patterns of symptoms might facilitate understanding of the30 underlying biological mechanisms.31 Objective32 To examine associations between allergic disease-related variants identified in a recent genome-wide33 association study and latent classes of allergic diseases (LCADs) in two population-based birth cohorts.34 Methods35 Eight previously defined LCADs: ‘No disease’, ‘Atopic march’, ‘Persistent eczema and wheeze’, ‘Persistent36 eczema with later-onset rhinitis’, ‘Persistent wheeze with later-onset rhinitis’, ‘Transient wheeze’, ‘Eczema37 only’ and ‘Rhinitis only’ were used as the study outcome.38 Weighted multinomial logistic regression was used to estimate associations between 135 SNPs (and a39 polygenic risk score, PRS) and LCADs among 6,345 individuals from The Avon Longitudinal Study of Parents40 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.ResultsWe found strong evidence for differential genetic associations across the LCADs; pooled PRS heterogeneity p-value=3.3x10-14, 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 associated with all LCADs that included eczema, but with stronger associations for LCADs with comorbid wheeze and rhinitis. The GSDMB locus in contrast was only associated with LCADs with wheeze.Conclusions & Clinical RelevanceWe 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.