Excessive Unbalanced Meat Consumption in the First Year of Life Increases Asthma Risk in the PASTURE and LUKAS2 Birth Cohorts

Abstract

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 4th and 12th 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.

Relationship between gut microbiota and lung function decline in patients with chronic obstructive pulmonary disease: a 1-year follow-up study

“…We found a significant increase in the mean proportion of Acinetobacter after 1 year in the control group. A previous study that investigated food introduced in the first year of life and subsequent asthma development showed that unbalanced meat consumption fostered growth of iron scavenging bacteria, such as Acinetobacter , which was related to asthma [ 39 ]. However, the biological mechanism remains unknown.…”

Early infant feeding and allergic respiratory diseases in Ibb city, Yemen

“…Also Yu et al report OR of 1.27 within Chinese children [ 24 ]. Moreover, it was found elevated risk of asthma at age 6 within children consuming meat at the first year of live by an OR of 8.47 [ 25 ]. Previously, a study concluded that an introduction of milk other than breast milk during the first 6 months after birth increased almost two fold the risk of development of persistent asthma [Adjusted Relative Risk (ARR): 1.71] [ 26 ].…”

Effects of Early Diet on the Prevalence of Allergic Disease in Children: A Systematic Review and Meta-Analysis

“…The risk of bias in randomized controlled trial (RCT) studies was assessed using the Cochrane Collaboration Risk of Bias tool [ 21 ], and the risk of bias in non-RCT trials was assessed using the Risk of Bias in Nonrandomized Studies of Interventions tool [ 22 ]. For all study reports, the summary Tables ( Supplemental Tables 1 and 2 ) [ [8] , [9] , [10] , [11] , [13] , [14] , [15] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] , [62] , [63] , [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] , [72] , [73] , [74] , [75] , [76] , [77] , [78] , [79] , [80] ,…”