Intestinal Dysbiosis in the Infant and the Future of Lacto-Engineering to Shape the Developing Intestinal Microbiome

PurposeThe goal of this study was to review the role of human milk in shaping the infant intestinal microbiota and the potential of human milk bioactive molecules to reverse trends of increasing intestinal dysbiosis and dysbiosis-associated diseases.MethodsThis narrative review was based on recent and historic literature.FindingsHuman milk immunoglobulins, oligosaccharides, lactoferrin, lysozyme, milk fat globule membranes, and bile salt–stimulating lipase are complex multifunctional bioactive molecules that, among other important functions, shape the composition of the infant intestinal microbiota.ImplicationsThe co-evolution of human milk components and human milk–consuming commensal anaerobes many thousands of years ago resulted in a stable low-diversity infant microbiota. Over the past century, the introduction of antibiotics and modern hygiene practices plus changes in the care of newborns have led to significant alterations in the intestinal microbiota, with associated increases in risk of dysbiosis-associated disease. A better understanding of mechanisms by which human milk shapes the intestinal microbiota of the infant during a vulnerable period of development of the immune system is needed to alter the current trajectory and decrease intestinal dysbiosis and associated diseases.     

Development and validation of the EUROFORGEN NAME (North African and Middle Eastern) ancestry panel

Inference of biogeographic origin is an important factor in clinical, population and forensic genetics. The information provided by AIMs (Ancestry Informative Markers) can allow the differentiation of major continental population groups, and several AIM panels have been developed for this purpose. However, from these major population groups, Eurasia covers a wide area between two continents that is difficult to differentiate genetically. These populations display a gradual genetic cline from West Europe to South Asia in terms of allele frequency distribution. Although differences have been reported between Europe and South Asia, Middle East populations continue to be a target of further investigations due to the lack of genetic variability, therefore hampering their genetic differentiation from neighboring populations. In the present study, a custom-built ancestry panel was developed to analyze North African and Middle Eastern populations, designated the ‘NAME’ panel. The NAME panel contains 111 SNPs that have patterns of allele frequency differentiation that can distinguish individuals originating in North Africa and the Middle East when combined with a previous set of 126 Global AIM-SNPs.     

The Health Belief Model in predicting healthcare workers' intention for influenza vaccine uptake in Jordan

BackgroundTheories of health behavior change are being inadequately adopted to understand the reasons behind low influenza vaccination rates among healthcare workers (HCWs). The Theory of Planned Behavior (TPB) is being used to predict intention-behavior relationship while the Health Belief Model (HBM) is being employed to predict actual behavior. The purpose of this study was to test a conceptual model based on the HBM’s constructs to predict Jordanian HCWs’ intentions for influenza vaccine uptake as an alternative to the TPB.MethodA cross-sectional questionnaire-based study was conducted in 2016 in a tertiary teaching hospital in Amman-Jordan including a convenience sample of 477 HCWs with direct patient contact. The study instrument was tested for validity and reliability. A conceptual regression model was proposed incorporating the constructs of the primary HBM with some modifications in the threat construct as well as an additional variable about explicit past vaccination behavior (in the past year and/or any previous history of influenza vaccine uptake).ResultsAlmost all the constructs of the HBM demonstrated significant differences between participants intending and those who did not intend to vaccinate against influenza. After adjusting for the confounding variables in the final conceptual regression model, past vaccination behavior (OR= 4.50, 95%Confidence Interval 3.38–6.00, P< 0.0005) and the perceived benefit scale (OR= 1.19, 95% Confidence Interval 1.11–1.28, P< 0.0005) were the only significant predictors of intentions to vaccinate against influenza in the next season.ConclusionTaking into consideration the altruistic beliefs of HCWs and their explicit past vaccination history augments the utility of the original HBM tool in predicting HCWs’ intentions to vaccinate against influenza in a way that is consistent with the predictive ability of the Theory of Planned Behavior.