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Background: Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated., Results: We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach., Conclusion: The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Background: The acquisition of a modern lifestyle may explain variations in asthma prevalence between urban and rural areas in developing countries. However, the effects of lifestyle on asthma have been investigated as individual factors with little consideration given to the effects of lifestyle as a set of attributes. The aim of the present study was to identify modern lifestyle domains and assess how these domains might explain wheeze prevalence in urban and rural areas., Methods: We analysed data from cross-sectional studies of urban and rural schoolchildren in Esmeraldas Province, Ecuador. Variables were grouped as indicators of socioeconomic factors, sedentarism, agricultural activities and household characteristics to represent the main lifestyle features of the study population. We used multiple correspondence analyses to identify common lifestyle domains and cluster analysis to allocate children to each domain. We evaluated associations between domains and recent wheeze by logistic regression., Results: We identified 2-3 lifestyle domains for each variable group. Although wheeze prevalence was similar in urban (9.4%) and rural (10.3%) schoolchildren, lifestyle domains presented clear associations with wheeze prevalence. Domains relating to home infrastructure (termed transitional, rudimentary, and basic urban) had the strongest overall effect on wheeze prevalence in both urban (rudimentary vs. basic urban, OR = 2.38, 95% CI 1.12-5.05, p = 0.024) and rural areas (transitional vs. basic urban, OR = 2.02, 95% CI 1.1-3.73, p = 0.024; rudimentary vs. basic urban, OR = 1.88, 95% CI 1.02-3.47, p = 0.043). A high level of sedentarism was associated with wheeze in the rural areas only (OR = 1.64, 95% CI 1.23-2.18, p = 0.001)., Conclusions: We identified lifestyle domains associated with wheeze prevalence, particularly living in substandard housing and a high level of sedentarism. Such factors could be modified through programmes of improved housing and education. The use of lifestyle domains provides an alternative methodology for the evaluation of variations in wheeze prevalence in populations with different levels of development.

Background: Helminths are modulators of the host immune system, and infections with these parasites have been associated with protection against allergies and autoimmune diseases. The human host is often infected with multiple helminth parasites and most studies to date have investigated the effects of helminths in the context of infections with single parasite or types of parasites (e.g. geohelminths). In this study, we investigated how co-infections with three nematodes affect markers of allergic inflammation and asthma in children. We selected Ascaris lumbricoides and Trichuris trichiura, two parasites that inhabit the human intestine and Toxocara spp (Toxocara canis and/or T. cati), intestinal roundworms of dogs and cats that cause systemic larval infection in humans. These parasites were selected as the most prevalent helminth parasites in our study population., Results: 36.4% of children were infected with one parasite; 12.7% with 2 and 5.2% with 3. Eosinophilia>4% and >10% was present in 74.3% and 25.5% of the children, respectively. Total IgE>200 IU/mL, sIgE≥0.70 kU/L and SPT positivity were present in 59.7%, 37.1% and 30% of the children, respectively. 22.7% had recent asthma (12.0% non-atopic and 10.7% atopic). Helminth infections were associated in a dose-dependent way to decrease in the prevalence of SPT and increase in eosinophilia, total IgE, and the production of the regulatory cytokine IL-10 by unstimulated peripheral blood leukocytes. No association with asthma was observed., Conclusions: Helminth co-infections in this population were associated with increased markers of the Th2 immune response, and with a host immune regulatory phenotype that may suppress allergic effector responses such as immediate hypersensitivity reactions in the skin.