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A higher diversity of food items introduced in the first year of life has been inversely related to subsequent development of asthma. In the current analysis, we applied latent class analysis (LCA) to systematically assess feeding patterns and to relate them to asthma risk at school age. PASTURE (N=1133) and LUKAS2 (N=228) are prospective birth cohort studies designed to evaluate protective and risk factors for atopic diseases, including dietary patterns. Feeding practices were reported by parents in monthly diaries between the 4 th and 12 th month of life. For 17 common food items parents indicated frequency of feeding during the last 4 weeks in 4 categories. The resulting 153 ordinal variables were entered in a LCA. The intestinal microbiome was assessed at the age of 12 months by 16S rRNA sequencing. Data on feeding practice with at least one reported time point was available in 1042 of the 1133 recruited children. Best LCA model fit was achieved by the 4-class solution. One class showed an elevated risk of asthma at age 6 as compared to the other classes (adjusted odds ratio (aOR): 8.47, 95% CI 2.52-28.56, p = 0.001) and was characterized by daily meat consumption and rare consumption of milk and yoghurt. A refined LCA restricted to meat, milk, and yoghurt confirmed the asthma risk effect of a particular class in PASTURE and independently in LUKAS2, which we thus termed unbalanced meat consumption (UMC). The effect of UMC was particularly strong for non-atopic asthma and asthma irrespectively of early bronchitis (aOR: 17.0, 95% CI 5.2-56.1, p < 0.001). UMC fostered growth of iron scavenging bacteria such as Acinetobacter (aOR: 1.28, 95% CI 1.00-1.63, p = 0.048), which was also related to asthma (aOR: 1.55, 95% CI 1.18-2.03, p = 0.001). When reconstructing bacterial metabolic pathways from 16S rRNA sequencing data, biosynthesis of siderophore group nonribosomal peptides emerged as top hit (aOR: 1.58, 95% CI 1.13-2.19, p = 0.007). By a data-driven approach we found a pattern of overly meat consumption at the expense of other protein sources to confer risk of asthma. Microbiome analysis of fecal samples pointed towards overgrowth of iron-dependent bacteria and bacterial iron metabolism as a potential explanation., Competing Interests: EvM reports to have received personal fees from PharmaVentures, OM Pharma, Springer-Verlag, Elsevier, Peptinnovate, Turun Yliopisto, Tampereen Yliopisto, Helsingin Yliopisto, European Respiratory Society, Deutsche Pharmazeutische Gesellschaft, Massachusetts Medical Society, the Chinese University of Hong Kong, European Commission, Boehringer Ingelheim, Universiteit Utrecht Faculteit Diergeneeskunde, Universität Salzburg, Georg Thieme Verlag, Japanese Society of Pediatric Allergy and Clinical Immunology, Nestlé Deutschland and HiPP, outside of the submitted work, and has received funding and research support from FrieslandCampina. In addition, EvM has patent LU101064 (Barn dust extract for the prevention and treatment of diseases) pending, royalties paid to ProtectImmun for patent EP2361632 (Specific environmental bacteria for the protection from and/or the treatment of allergic, chronic inflammatory and/or autoimmune disorders, granted on 19 March 2014), and patents EP1411977 (Composition containing bacterial antigens used for the prophylaxis and the treatment of allergic diseases, granted on 18 April 2007), EP1637147 (Stable dust extract for allergy protection, granted on 10 December 2008), and EP 1964570 (Pharmaceutical compound to protect against allergies and inflammatory diseases, granted on 21 November 2012) licensed to ProtectImmun. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Hose, Pagani, Karvonen, Kirjavainen, Roduit, Genuneit, Schmaußer-Hechfellner, Depner, Frei, Lauener, Riedler, Schaub, Fuchs, von Mutius, Divaret-Chauveau, Pekkanen and Ege.)

Rationale: Clinical and epidemiologic approaches have identified two distinct sets of classifications for asthma and wheeze phenotypes., Objectives: To compare epidemiologic phenotype definitions identified by latent class analysis (LCA) with clinical phenotypes based on patient histories, diagnostic work-up, and treatment responses. To relate phenotypes to genetic and environmental determinants as well as diagnostic and treatment-related parameters., Methods: LCA was performed in an international multicenter birth cohort based on yearly questions about current wheeze until age 6 years. Associations of wheeze classes and clinical phenotypes with asthma-related characteristics such as atopy, lung function, fraction of exhaled nitric oxide, and medication use were calculated using regression models., Measurements and Main Results: LCA identified five classes, which verified the clinically defined wheeze phenotypes with high sensitivity and specificity; the respective receiver operating characteristics curves displayed an area under the curve ranging from 84% (frequent wheeze) to 85% (asthma diagnosis) and 87% (unremitting wheeze) to 97% (recurrent unremitting wheeze). Recurrent unremitting wheeze was the most specific and unremitting wheeze at least once the most sensitive definition. The latter identified a subgroup of children with decreased lung function, increased genetic risk, and in utero smoke exposure (ODDS RATIO, 2.03; 95% CONFIDENCE INTERVAL, 1.12-3.68; P = 0.0191), but without established asthma diagnosis and treatment., Conclusions: Clinical phenotypes were well supported by LCA analysis. The hypothesis-free LCA phenotypes were a useful reference for comparing clinical phenotypes. Thereby, we identified children with clinically conspicuous but undiagnosed disease. Because of their high area under the curve values, clinical phenotypes such as (recurrent) unremitting wheeze emerged as promising alternative asthma definitions for epidemiologic studies.